Government: From the routine to the critical

Social media use by government: From the routine to the critical
Andrea L. Kavanaugh a,1
, Edward A. Fox a,2
, Steven D. Sheetz b,3
, Seungwon Yang a,
⁎, Lin Tzy Li d,e,4,5,6
Donald J. Shoemaker c,7
, Apostol Natsev f,8
, Lexing Xie g,8,9
a Department of Computer Science, Virginia Tech, VA 24061, USA
b Department of Accounting and Information Systems, Virginia Tech, VA 24061, USA
c Department of Sociology, Virginia Tech, VA 24061, USA
d Institute of Computing, University of Campinas, Campinas, SP 13083–852, Brazil e Telecommunications Res. and Dev. Center, CPqD Foundation, Campinas, SP 13086–902, Brazil f Google, 1600 Amphitheatre Parkway, Mountain View, CA 94043, USA
g Australian National University, Canberra, Australia
article info abstract
Available online 11 August 2012
Digital government
Social media
Crisis informatics
Information visualization
Word cloud
Focus group study
Civic organizations
Social media and online services with user-generated content (e.g., Twitter, Facebook, Flickr, YouTube) have
made a staggering amount of information (and misinformation) available. Government officials seek to leverage these resources to improve services and communication with citizens. Significant potential exists to identify issues in real time, so emergency managers can monitor and respond to issues concerning public safety.
Yet, the sheer volume of social data streams generates substantial noise that must be filtered in order to detect meaningful patterns and trends. Important events can then be identified as spikes in activity, while event
meaning and consequences can be deciphered by tracking changes in content and public sentiment. This
paper presents findings from a exploratory study we conducted between June and December 2010 with government officials in Arlington, VA (and the greater National Capitol Region around Washington, D.C.), with
the broad goal of understanding social media use by government officials as well as community organizations, businesses, and the public at large. A key objective was also to understand social media use specifically
for managing crisis situations from the routine (e.g., traffic, weather crises) to the critical (e.g., earthquakes,
© 2012 Elsevier Inc. All rights reserved.
1. Introduction
Citizens are increasingly relying on social media for communication
with their family, friends, colleagues, businesses, and the government.
The capabilities to facilitate interpersonal and group interaction provide
new and unique opportunities for community leaders, elected officials,
and government service providers to inform, and be informed by, the
citizenry (Golbeck, Grimes, & Rogers, 2010). Twitter, Facebook, Flickr,
YouTube, and other services with user-generated content have made
a staggering amount of information available online. In 2010, during
the period of our study, Twitter was generating an estimated 55 million
tweets a day (“Twitter blog: Measuring tweets, 2010”), Flickr was
amassing more than 6000 photos each minute (“Flickr, 2010”;
Smarter Transportation: 10 Social Media Tools to Navigate Your City,
2010; “YouTube Blog, 2011”), YouTube was accumulating over 60
hours of video per minute (“YouTube blog. Holy Nyans! 60 h per minute and 4 billion views a day on YouTube”), taking up more than 10%
of all internet traffic, and Facebook had more than 400 million active
users; by early 2012 the number of Facebook users had more than doubled to 845 million (Protalinski, 2012), making it the most visited site
on the Internet in the US. All this information and deep reach are readily
available for government officials to tap into and leverage for improved
Government Information Quarterly 29 (2012) 480–491
⁎ Corresponding author at: Department of Computer Science, 114 McBryde Hall,
Mail Code 0106, Virginia Tech, Blacksburg VA 24061, USA.
E-mail addresses: [email protected] (A.L. Kavanaugh), [email protected] (E.A. Fox),
[email protected] (S.D. Sheetz), [email protected] (S. Yang), [email protected],
[email protected] (L.T. Li), [email protected] (D.J. Shoemaker),
[email protected] (A. Natsev), [email protected] (L. Xie). 1 Department of Computer Science, 2202 Kraft Drive Mail Code 0902, Virginia Tech,
Blacksburg VA 24060. Tel.: +1 540 231 1806; fax: +1 540 231 9218.
2 Department of Computer Science, 114 McBryde Hall, Mail Code 0106, Virginia
Tech, Blacksburg VA 24061. Tel.: +1 540 231 5113.
3 Department of Accounting and Information Systems, Pamplin Hall 3080 Mail Code
0101, Virginia Tech, Blacksburg, VA 24061. Tel.: +1 540 231 6096; fax: +1 540 231
4 This author was with Department of Computer Science, Virginia Tech, VA 24061
when this work was performed.
5 Institute of Computing, University of Campinas, Av. Albert Einstein, 1251 – Campinas/
SP – Brazil, 13083–852. Tel.: +55 19 3521 5887. 6 CPqD Telecommunications R&D Center, Rodovia Campinas – Mogi-Mirim (SP-340)
– km 118,5 – Campinas/SP – Brazil, 13086–902. Tel.: +55 19 3705 7136. 7 Department of Sociology, 512 McBryde Hall, Virginia Tech, Blacksburg, VA
24061–0137. Tel.: +1 540 231 8971. 8 This author was with IBM Watson Research Center, Hawthorne, NY 10532 when
this work was performed.
9 Current address: Bldg 108 Australian National University, Acton, ACT 0200,
0740-624X/$ – see front matter © 2012 Elsevier Inc. All rights reserved.
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services. However, the treasure trove of information comes with substantial noise that must be filtered to make this information useful
and reliable.
Government officials seek to leverage these resources to improve
services and communication with citizens, especially segments of
the population that previously were difficult to reach and underrepresented (Bertot, Jaeger, & Hansen, 2012). Yet, the sheer volume of
social data streams generates substantial noise that must be filtered
to be useful. The desire and potential exist for identifying and
responding to issues in real time for more effective emergency management as well as improved public safety and general quality of
life. For example, critical events of interest (e.g., earthquake, flash
mob gatherings, protests, etc.) can be identified as spikes in the social
media volume. Issues of concern for public safety or general quality of
life (e.g., traffic, air quality) can be discovered, monitored, and mitigated by analyzing social media streams to detect meaningful patterns and trends (Fig. 1).
Similarly, monitoring these patterns and themes over time could
provide officials with insights into the perceptions and mood of the
community that cannot be collected through traditional methods
(e.g., phone or mail surveys) due to a variety of reasons, including
the prohibitive cost and limited reach of traditional methods as well
as the limited window of opportunity for influencing or mitigating
events as they evolve. Perhaps most importantly for emergency management, no traditional method can provide insight in real time. Surveys require substantial time and effort prior to data collection,
during the collection process, and for analyses of the results, which
often take months to complete. Secondly, substantive costs are associated with survey activities, making them especially difficult in
light of reduced and shrinking budgets of governments at all levels.
Finally, once completed a survey captures perceptions at a single
point in time. Although it is possible to use surveys at intervals to
monitor progress, it is not a common practice, substantially increases
costs, and often does not reach important segments of the citizenry.
Data mining of diverse real-time feeds of social streams related to
real-world events is needed to enable officials to make sense of the
vast amount of information generated. In so doing, government should
be able to act more effectively on matters both routine (e.g., ongoing issues of public concern) and critical (e.g., major weather or traffic disruption, public safety or rapid response). Using social media, we can answer
questions that are not normally addressed by the gather-and-report
style of journalism involving traditional sources, such as: When and
where are events of importance currently happening? What are the different views of a given event? Who are the influential users in an online
or local community? Yet, to use these resources effectively, we first need
to address a series of questions including: Which social media should
government use to communicate most effectively with a diverse public?
How should messages be formed and framed across social media to be
effective? To what extent can messages in social networks be used to explain how influential messages form and spread? Is civic information,
disseminated through social media as opposed to through the Web or
email, more likely to reach some traditionally underrepresented groups,
such as those with lower socio-economic status (SES) or younger
voters? What role do social media play in the general mix of information
sources for citizens to communicate about civic life, with each other and
with government? Do social media affect civic participation and if so, for
whom and what kinds of civic participation?
We seek to leverage technology to help government manage information and facilitate interaction in meaningful ways in order to
achieve broader public participation than is possible through normal
channels (e.g., public commenting at county board meetings). Deep
analysis of social media streams can also provide access to segments
of the community that have not participated in traditional ways.
This exploratory study was part of a larger investigation funded by
NSF (IIS-0916733) to build a Crisis, Tragedy, and Recovery Network
(CTRnet) (“CTRnet: Crisis, Tragedy, & Recovery, 2010”). In collaboration with Arlington Virginia County government, we conducted a
six-month exploratory study of how social media were being used
by local citizens, community organizations and government, and
how data analysis could be applied in Arlington and environs to improve services and communication with citizens. Our primary research objectives were to investigate the use and impact of social
media and to identify and develop methods to effectively meet a variety of local government and community needs.
Fig. 1. Social media streams to improve services and communication with citizens.
A.L. Kavanaugh et al. / Government Information Quarterly 29 (2012) 480–491 481
Specifically, we have begun to:
1) Leverage and further refine tools for collecting and correlating
large amounts of public social media data relevant to Arlington
County, VA and environs,
2) Archive and curate collected social media data over a period of
time into a digital library, including social media for crisis conditions, and
3) Identify, research and implement applications of multimedia analytics and text mining for government services and communication.
To address these goals we crawled, collected, aggregated, and archived relevant social media data; we conducted exploratory focus
group interviews with key stakeholders in government and community organizations, and developed tools to analyze and render data
more usable and meaningful for local organizations, governments
and citizens.
Our target information sources included official Arlington County
Facebook pages, Twitter feeds (“Arlington County Blog Central, 2010”;
“Arlington County Facebook Profile, 2010”; “Arlington County Flickr
account, 2010”; “Arlington County News on Twitter, 2010”; “Arlington
County & VA Official Site, 2010”; “See-Click-Fix in Arlington County,
2010”), blogs, news, community forums, and relevant postings by the
public on social media sites such as Twitter, Facebook, YouTube, and
Flickr. Applications of such analyses could include monitoring public
opinion before and after large public events, monitoring planned or
unplanned activities, identifying and categorizing important community
issues over time and location, enhancing community recovery in
response to crises or tragedies, and tracking the development of
long-running themes in civil life.
While many government agencies have recognized social media
as an important information source and outlet, there has yet to be a
comprehensive account about the needs and methods for social
media use. Recent case studies, such as published by Queensland
Police Service (“Queensland Police Service, 2011”) outlined the
experiences and best practices for engaging and informing citizens
during a historic flood. To the best of our knowledge, this study is
the first to survey across a wide range of government agencies and
community organizations, supported by data analysis of existing online interactions.
The CCSR is a partnership among Virginia Tech, IBM, and Arlington
County. Based on interests and needs demonstrated in a CCSR workshop with officials from Arlington County and the National Capital
Region (NCR) (the area around Washington, D.C.), we planned the
exploratory study in collaboration with IBM and Arlington County
government to explore social media applications that might improve
community resilience in times of crises, as well as provide timely and
complementary open sources of information for facilitating city,
county, and community services. Further, we explored social media
applications that might help agencies make sense of a deluge of information by providing meaningful consumable insights.
2. Social Media and Government
Social media are internet-based applications designed to facilitate
social interaction and for using, developing and diffusing information
through society. Social media build on many of the same concepts and
technologies of Web 2.0, most basically, the creation and exchange of
user generated content (O’Reilly, 2007). There is much overlap between the two concepts and technologies in terms of examples, including blogs, wikis, and recommender systems; websites to share
videos, music, pictures and podcasts; and social networking sites
such as Facebook and MySpace. Broadly, Web 2.0 and social media
are considered social software, i.e., software that enables people to
rendezvous, connect, or collaborate through computer-mediated
communication (Boyd & Ellison, 2007; Lampe, Ellison, & Steinfield,
2006). This type of software has existed for years in the form of online
bulletin board systems listservs, forums, and newsgroups. More recently, however, blogs (Tepper, 2003) and microblogs (e.g., Twitter),
RSS feeds, tagging systems (Furnas et al., 2006), and collaborative filters have made social software easy to use and highly scalable leading
to greater adoption and use.
2.1. Social Media Use by Citizens
Social media have changed the way many Americans get information about what’s going on in their communities, and national and
global current events. They provide new ways for citizens to share information and to interact with each other and with elected officials
and government agencies. A national study conducted by Pew Internet & American Life in 2010 finds that almost a third (31%) of all
online adults in the USA used social tools such as blogs, social networking sites, and online video as well as email and text alerts to
keep informed about government activities (Smith, 2010).
Social media seem to have particular appeal for groups that have historically lagged in their use of other online government offerings — in
particular, minority Americans (Smith, 2010). Latinos and African
Americans are just as likely as whites to use these tools to keep up
with government, and are much more likely to agree that government
outreach using these channels makes government more accessible
and helps people be more informed about what government agencies
are doing. Findings from the 2010 Pew study also show that 40% of
adult Internet users have gone online for raw data about government
spending and activities. This includes anyone who has done at least
one of the following: looked online to see how federal stimulus
money is being spent (23% of internet users); read or downloaded the
text of legislation (22%); visited a site such as that provides access to government data (16%); or looked online to see who is contributing to the campaigns of their elected officials (14%).
In a 2009 online convenience sample survey conducted in the US by
the American Red Cross (“American Redcross: Social Media in Disasters
and Emergencies”), 75% of respondents reported they would use social
media in crisis and civic-related situations (e.g., traffic jam, car crash,
potential crime, or downed power lines). Nearly half of respondents
reported that they would use social media to let others know they
were safe in an emergency; 86% report they would use Facebook; 28%
would use Twitter, and 11% would use a blog. Solutions that are
(already) provided by the industry for public safety include call processing products and notification systems. For example, Plant CML offers
call processing software that is used by 2/3 of all 911 centers in North
America. They also provide notification systems, computer-aided design & mapping, data management and analysis, information management, and land mobile radio. These systems, however, are mostly
based on phone communications and are not using the power of social
Large public gathering events, such as parades or demonstrations,
are examples of conditions of social convergence, that is, highintensity events with large population density and heightened security needs. Before the event it is beneficial to monitor online discussions on national and global sources, such as YouTube and Twitter,
as well as local sources, such as Arlington blog central (“Arlington
County Blog Central, 2010”), local Facebook pages, YouTube and Twitter posts (“Arlington County Facebook Profile;” “Arlington County
News on Twitter;” “Gasbuddy: Find local gas prices, 2010”), or Foursquare “check-ins” (or similar location-aware mobile media applications). This monitoring helps community leaders and the public stay
informed about the various perspectives, sentiments, feedback, and
insights around an event or an issue of interest. Afterwards, if a security event has emerged (e.g., violence or vandalism), sometimes evidence will be posted on photo and video sites, which can help local
officials identify and track suspects as an event progresses. In epidemic propagation and prevention, on the other hand, the focus of information management is on early spotting of cases and managing
482 A.L. Kavanaugh et al. / Government Information Quarterly 29 (2012) 480–491
public input, contributions, and feedback around issues like quarantine, vaccination, and distribution of sanitary advice (e.g., swine flu).
Research on the use of Twitter in crises has a short history, as Twitter
was established only in 2006. A form of micro-blogging, Twitter is a free,
short messaging service with some social networking features. Some of
the most relevant work to ours has been done by Palen, Hughes, and colleagues (Hughes & Palen, 2009; Hughes, Palen, Sutton, Liu, & Vieweg,
2008) and by Zuckerman on the Moldovan election protests in Africa
(Zuckerman, 2009). These studies specifically focus on the use of Twitter
during disasters and conditions of social convergence, such as mass political demonstrations, rallies or riots. Hughes et al. (Hughes & Palen, 2009)
report that Twitter use under duress and in crisis conditions of the two
hurricane episodes of Ike and Gustav in 2008 is distinct from routine general Twitter communication behavior in two ways: 1) fewer tweets are
sent as replies to other tweets; and 2) fewer URLs are included in the
tweet posts. They surmise that this is because in a crisis, people need to
broadcast information as widely as possible to as many people as possible at once (i.e., no need to reply to a specific individual) and people are
less likely to go to a website for additional information during an emergency. As an emergency is unfolding, Twitterers may broadcast more up
to date and timely information (and sometimes misinformation) than
government organizations and mainstream media that take the time to
double-check the accuracy of their public information, especially during
a crisis.
2.2. Social Media Use by Government
Twitter and other social sources have been effective in early event
spotting (Opsahl, 2010; Sakaki, Okazaki, & Matsuo, 2010), the response
time of which can be even faster than official sources (e.g., earthquake
reporting). Such monitoring strategies also can be used for epidemic
spotting and trending, where monitoring should be both distributed
and spanning a longer period of time, such as the first case in each
school district, resurgence of disease cases, and long-range planning
for local management. In the case of continuous monitoring, social
media can help measure the effectiveness of control measures and propaganda, e.g., if the public is embracing the vaccine distribution scheme,
complaining about it, or helping authorities stay better informed about
gaps or deficiencies in its administration.
We have been studying social media use and impact as part of an ongoing longitudinal investigation of Internet use and impact in Blacksburg,
Virginia and environs since the early 1990s (“Social Media Sells, 2010”).
Blacksburg is home to the main campus of Virginia Tech (which also has
a small campus in northern Virginia near Arlington) and is home to the
community computer network known as the Blacksburg Electronic
Village (BEV). Blacksburg town government has won several awards
for its rich mix of media to inform and communicate with citizens, including Twitter and Facebook since January 2009 as an additional channel for ‘Blacksburg Alerts’ available by email or text message. The
Communications Specialist in town government monitors Twitter
(using TweetDeck) for relevant posts that would benefit from a reply
(e.g., “the town does not have control over the old middle school in
Blacksburg, that is the County’s jurisdiction”) or should be brought to
the attention of town council as a citizen suggestion (“it would help to
have a cross walk painted at this intersection; it’s very busy”).
While this was not the case for the town of Blacksburg government, in the National Capitol Region focus group participants noted
that the public relations person for various government agencies
was typically not familiar with nor comfortable with social media.
This limitation makes it especially difficult for the public relations office to manage this channel of communication with the public.
From our preliminary study of social media use in Blacksburg, we
found that most often the person posting tweets or managing an
organization’s Facebook page was not from the organization’s leadership. Instead, a college student or other young adult was often working in tandem on behalf of the organization to post announcements,
updates, or other information. Some other US communities, including
our project partners at Arlington County, Virginia, are experimenting
with monitoring Twitter and Facebook using a Web tools like
TweetDeck and Hootsuite, in order to monitor social media communications and potentially to reduce workload and enhance responses
at 911 centers (Opsahl, 2010).
3. Study Methods
We collected and analyzed area-specific social media (social media)
sources, and conducted focus group interviews with 25 county officials
(specifically, personnel from emergency management services, the police department, and volunteer leadership office), including a questionnaire about their social media use and community involvement. We
were able to recruit 25 participants and organized them into three separate focus group sessions (lasting two hours each) held in November
and December 2010 in Arlington. At the outset of each of the interview
sessions, we asked participants to complete an online questionnaire.
The questionnaire asked them about their use of social media and
their involvement in the local community.
The focus group sessions proceeded in two main stages. They
began with participants engaged in electronic brainstorming to generate a number of ideas quickly, followed by a process whereby
they identified categories that grouped the ideas by similarity.
Using individual computers with group support software that we
developed, the focus group participants anonymously generated and
entered ideas, beliefs, issues, or concepts, in the form of short sentences or phrases that they felt were important to the situation. We
provided them with a set of framing questions we developed to cue
participants to begin entering ideas. Fig. 2 shows the framing questions we used in the focus groups. The ideas participants generated
were shared with other participants as they were generated, allowing
ideas generated by one person to be expanded by others or to cue
others to generate related ideas. Participants then worked together
with the facilitator to create and name the units or categories that organized their ideas by similarity.
We collected social media in the form of official posts and public
comment data from the Arlington County Facebook page, Twitter
feeds from local civic organizations, YouTube videos, and crawls and
searches of local web pages. We used different Twitter analytical
tools, such as ‘140 kit’ ( and the Archivist
( to collect tweets from 34 local organizations, including Arlington government, that were civic in nature
(rather than commercial or residential).
We performed semantic analyses on the Twitter data to identify
popular topics and to characterize followers by their profile data;
we conducted simple frequency counts to calculate number of ‘followers’ and ‘followers of followers’ of a given organization. We used
the visualization software ‘wordle’ ( to represent the results of the Twitter analyses as tag clouds in order to
be able to distill and make greater sense of large amounts of data
more quickly and easily. For the YouTube video collections, we used
a Perl script to search all YouTube videos for the tags or video with
the title ‘Arlington County’ and represented the search results in a
tag cloud indicating the most frequent tags in the image collection.
4. Results
Our findings from the exploratory study are based on the focus
group interviews and participant questionnaires (N=25), and the
development of tools to analyze social media data we collected. The
results fall into three main areas:
1) Local government uses social media without knowing its costs and
benefits, or who their actual audience is, who in their organization
should monitor communications, how and when they should be
A.L. Kavanaugh et al. / Government Information Quarterly 29 (2012) 480–491 483
responding, and what effect their social media communications
have on the public;
2) New tools are needed to help government and citizens make sense
of the overwhelming amount of data that is being generated, to
model the flow of information, and to identify patterns over
time; and
3) Digital libraries are needed to archive and curate generated content, especially for crisis and social convergence situations, but
also for analyses that cover longer time frames.
4.1. Focus Group Questionnaire
Each of the 25 focus group participants completed an onlinequestionnaire at the outset of their focus group interview session.
Of this sample, 15 (60%) were female and 10 (40%) were male. The
majority (84%) was white, non-Hispanic. Sixty-four percent were
married and 92% were employed on a full-time basis. It is reasonable
to characterize the interviewees as civically active, as they reported
being very active in their community and being well informed
about local news and politics. Seventy-six percent reported that
they kept up with local news daily.
Most respondents reported they have ideas for improving things
in their community at least once a month (76%) and that they frequently get together with others who are well informed about local
issues. Thirty-six percent reported that they worked to bring about
change in their community on a daily basis. Almost half of the participants (48%) reported that they either posted comments online,
posted pictures or video online, or blogged about a political or social
issue in the past year.
The overwhelming majority (80%) of respondents reported having
a profile on at least one type of social media website (social networking site, blog or Twitter, photo/video collections, place-based applications, or other). All of these profile-users maintained a profile on a
social networking site, with many having profiles on multiple types
of social media sites.
Respondents used social networking sites more frequently than
other types of social media sites. Over half (56%) of respondents
used social networking sites on a daily basis, and 76% used these
sites at least once a week. Place-based applications were the least
used type of site. Of the 5 individuals who used these applications,
none used these sites more than once a month. Most respondents
accessed these social media sites via personal computer (96%) and
many used their cell-phones, too (68%).
Social media use was fairly well distributed across types of social
media sites, with the exception of place-based application (social networking sites 56%, blog or microblog 44%, and photo/video collection
40%). All in all, 64% reported using social media sites to communicate
with other members of their organization, with several respondents
utilizing multiple types. Fifty-two percent reported using social
media sites for such purposes at least once a week.
The respondents were generally satisfied (88%) with current
emergency response efforts in their community. All respondents felt
that the county government should contact citizens by way of
phone call or text message during a crisis. Eighty-four percent felt
that social networking sites also should be utilized for this purpose,
and 72% felt that blogs or microblogs (e.g., Twitter, Tumblr) should
be as well. Over half (56%) of respondents reported that they were
at least somewhat likely to use one or more types of social media to
contact family members during a crisis. However, only 24% were likely to report a crisis to local government agencies via social media. The
majority of respondents reported that talking to others in person or
by telephone was the most important source of local information.
4.2. Focus Groups: Information Factors
In the electronic brainstorming step of the focus groups, participants identified 23 categories of factors related to 1) the organization
and 2) the information exchanged between the organization and
community (Fig. 3). Information factors include issues related to the
quality and quantity of information generated through social media.
They also include the tone and types of communications in which
government seeks to participate, including outreach, feedback, and
two-way communication. Additional types of information that can
be obtained from some social media channels, e.g., detecting the locale of emerging events, are of substantial interest for emergency
management and policing functions. Finally, technology issues included the security of the technology used to provide social media
and other new tools, and the need to meet legal obligations for saving
public records. Further, substantial questions remained among participants regarding which social media should be utilized for diverse audiences and purposes.
Together the factors identified by the participants describe a broad
range of interests and concerns of the Arlington County government
in relation to their use of social media. Each of these categories also
contains a set of ideas from the electronic brainstorming that further
clarifies the intentions of the participants about the meaning of the
4.3. Focus Groups: Organization Factors
The organization factors that focus group participants identified include policies, legal issues, costs and training (Fig. 3). The organization
requires that polices be adopted to provide the environment needed
for employees to achieve work objectives. Management buy-in is essential if benefits are to be realized and costs are to be controlled. To utilize
social media effectively, employee activities and roles are institutionalized through Human Resources (HR) to clarify job descriptions and ensure related types of communication are managed effectively. There
are also attempts to control information and to communicate the
government’s opinions and actions to the public.
• What are the missions and objectives of your organization?
• What are you trying to accomplish using social media?
– Do you feel you are currently accomplishing this goal effectively with social
media? (if yes, why?)
– If not, what do you need [to know?– to do? –in order] to use social media more
• What concerns do you have about using social media?
• What difficulties do you have about using social media?
• What information would you like to have about how your organization uses social
• What information would you like to have about how social media is being used in your
• Is there anything else you would like to know about social media that would be helpful?
Fig. 2. Framing questions for focus group interviews.
484 A.L. Kavanaugh et al. / Government Information Quarterly 29 (2012) 480–491
Organizations seek to define the types of information to be shared
and the manner of sharing. The participants perceive the substantive
legal issues related to maintaining government transparency, often
through the Freedom of Information Act (FOIA), as important in considering the use of social media. For example, should tweets by a
government employee be part of the public record? What about tweets
by a government employee that are related to their non-work life? The
individual government employee should set up two different identities
in Twitter, in order to separate professional and private roles and
Public Record/FOIA (are SM public record, tools needed to save, outdated
Resource Issues (SM adds to previously full time job, other duties, limit
24/7 expectation)
ROI/cost to value (how to measure value, who are we reaching, enough
received messages)
Education (tools to manage, learning from each other, train constituents
where to go)
Training (best practices for dividing duties, case studies, understanding
management’s concerns)
Other (educate nonusers, establish boundaries)
Information Factors
Community Outreach (emergency, crime/traffic alerts, 24/7 level of
service, recruitment)
Feedback (from community to organization, social trends, locale, fast
spreading ideas)
Population Reached (misses traditional/older population or can’t afford
One Way vs. Two Way (pushing out vs. creating dialogue, effort/costs
Tone (Government presents just the facts, not stories, not press release,
listen then educate)
Quality of Content (accuracy, facts of situation, un-vetted information,
Quantity of messages (how to be heard, from 1 to 10 to 1000s,
overwhelming, loss of control)
Personal Level (information overload, ability to write complete thoughts,
nuances of face-to-face lost)
Security (network exposed to world)
Technology and Equipment (cost of technology and maintenance, cost
savings, training)
Social Media (SM) Outlets (knowing audience/expertise, users expect
transparency, so many outlets)
Public Record/FOIA (are SM public record, tools needed to save, outdated
Organization Factors
Management Buy-In (unknown expectations, under valued, need to set
Control Issues (how much to control, what we can control, telling
how/what to think/do)
Human Resource (HR) Components (job descriptions, evaluation,
expertise, dialogue, positive and negative)
SM Communications Policy (what not to do/say, right people to make
SOP, moving target)
Professional Level (privacy concerns, devices owned by county,
investigative purposes)
Legal Issues
Data Maintenance (FOIA data maintenance and related costs)
Owing Vs Using Someone Else (official outlet versus imposter, use in
Fig. 3. Simple taxonomy of categories identified by focus group participants.
A.L. Kavanaugh et al. / Government Information Quarterly 29 (2012) 480–491 485
Costs are always important to organizations, and government
budgets have been squeezed due to reduced receipts resulting from
slowing economic activity and increased use of government services.
Yet the participants perceive that the potential exists for achieving efficiencies using social media and the potential return on investments
should be evaluated. Complicating this calculation is the value placed
on reaching previously uninvolved constituents and the most interested participants. One of the costs of adopting social media is related
to training the employees who will use them. In addition, the public
must be educated to understand how the government will interact
with them and what expectations for interaction are appropriate.
Some of the Arlington County focus group participants said that they
need social media aggregation tools. In general, dashboard services that
accept search keywords and phrases help monitor information from
multiple social media, such as trackur (
social-media-monitoring) and Netvibes (
But these tools are designed to support businesses not government or
citizens, so they are not optimal for civic needs. Having geo-mapping
features would be very useful for the needs of cities and communities,
which are not currently enabled in dashboard tools.
Some emerging applications allow citizens to contribute geo-tagged
photos and video to a community database. For example, MIT’s Mobile
Media Experience Laboratory has developed a place-based application
called Locast for this purpose ( The video
analytic software IBM has developed will help to organize and cluster
images of similar content or location. This would make it easier for
users to find content of interest and to contribute to ongoing information exchange regarding a particular issue related to a specific place
(e.g., building a new school).
Some focus group participants also indicated that recent or projected budget cuts could erode 15 years of community outreach; the
County wanted to understand how to use technology to maintain
and sustain established communications with citizens. The Arlington
area homeowners and neighborhood/civic associations have been key
links for government to achieve community outreach in the past, but
not all neighborhoods have homeowners associations. Residential
neighborhoods lacking associations are usually characterized as having lower socio-economic status (SES) as measured by education
and income; with budget cuts it is even harder for government to sustain routine outreach and communication with these areas of the city.
Social media may be particularly helpful for outreach to such households and neighborhoods, especially through neighborhood opinion
leaders and cell phones.
Preliminary evidence from a national study by Pew Internet &
American Life (Smith, Verba, Brady, & Schlozman, 2009) indicates
that the use of social media for civic purposes is not as strongly correlated with education and income as the use of traditional internet
(i.e., web browsing and email). This may be because opinion leaders
(i.e., influential individuals) exist at all social strata, and they may
convey information to members of their social circles not only face
to face, but also by cell phone. Cell phone ownership permeates all social strata and exceeds computer ownership among lower SES groups.
The cell phone is essentially a pocket computer. For lower SES
groups it is likely to be the only computer they are using. While we
were not able to study cell phone use among lower SES groups in
this exploratory study, we are investigating cell phone use for civic
purposes among similar demographic groups in southwest Virginia
in related research. We are investigating the possible use of cell
phones to address information needs, and their connection to social
media, especially text messaging and image sharing between government, local opinion leaders and lower SES populations.
4.4. Tools for Analyzing Social Media Data
In order to study the pattern of communication and the information
communicated using social media, we collected publicly available data
from Twitter. We identified 34 civic organizations, some of which are
government agencies, in the National Capitol Region (NCR) that were
tweeting; we collected and analyzed their tweets for 30 days between
September and October 2010.
We analyzed the tweets as well as the biographical information
posted as profiles of the organizations’ followers using the Natural
Language Toolkit, tag clouds, and graphs. Fig. 4 shows the number
of followers for the 34 civic organizations in the NCR. In order to get
a sense of who are the followers of these 34 civic organizations, we
collected the publicly available biographical profile information that
followers list on their own Twitter accounts.
For the 34 civic organizations that were tweeting during the
September–October 2010 period, we see there were a total of about
31,000 ‘direct’ followers (i.e., people who subscribe to the RSS feed
that carries each organization’s Twitter posts). What is interesting
to note is that the ‘direct’ followers are themselves being ‘followed’
by other people — what we refer to as ‘followers of followers.’ The
number of followers of followers for these same organizations is
over 67 million (Fig. 5). By looking into the number of followers of
followers, we see the great extensibility of the communication
chain radiating out beyond the original tweet.
One of the 34 civic organizations, a local news and events group
called Arlington Unwired (Arlington UW) is shown with an arrow
in Fig. 4. It had only 471 followers on the date we captured these
data (September 26, 2010). We can see from the analysis of the number of Arlington UW followers’ followers (Fig. 5) there are over 8 million followers. This is not to say that a tweet from Arlington UW will
go beyond the 471 direct followers; however, if there is a crisis in the
Arlington area (such as a major catastrophe or extreme violence) it is
very likely that the indirect followers will retweet (forward along the
same Twitter post) regarding such a catastrophe to their own set of
followers (i.e., over 8 million followers). In this way, a critical piece
of information has the potential of being disseminated throughout a
community far beyond the direct followers to a larger population of
followers’ followers.
It is also important to note that among the followers of Arlington
UW is ‘Barak Obama’ — and the number of followers of ‘Barak Obama’
is over 5 million. Further analyses tell us which words are used most
commonly in the Arlington UW followers’ bios during this period. The
predominance of various words (most common words appear larger
in a tag cloud) provides a quick overview of what is being said or characterized (in the case of followers’ bios). Fig. 6 shows in a tag cloud the
predominant profile descriptors given by the followers of Arlington
This kind of profile analysis and visualization provides a quick
overview of the type of individuals and their interests who are following a given organization. We analyzed and visualized in a tag cloud
the 20 recent tweets of the followers of Arlington Unwired (UW) at
the time of the data capture (September 26, 2010) shown in Fig. 7.
By looking at the recent tweets of Arlington UW followers, we see
a kind of ‘mood’ and ‘buzz’ among users. The many references to time,
e.g., today, tomorrow, tonight, weekend, reveal a focus on things happening around the period that the tag cloud is generated. However,
the specific events presumably included in the tweets do not occur
often enough to be included in the tag cloud. The large ‘RT’ stands
for re-tweet, meaning that this is the most common term appearing
in the Twitter posts for these users. The organization knows from
this analysis that many of their posts are going well beyond their immediate (direct) followers.
Fig. 8 shows approximately 40 frequent words from the follower
profiles of CarFreeDiet, which is one of Arlington’s commuter services
that promote healthy and environment-aware life-styles without (or
less use of personal) cars. The organization’s Twitter profile says,
“Arlington’s Car-Free Diet is the easy, fun way to live a car-free lifestyle”.
Fig. 9 shows the most frequent words from the 20 ‘latest’ tweets
(at the time of data capture, September 2010) of the followers of
486 A.L. Kavanaugh et al. / Government Information Quarterly 29 (2012) 480–491
CarFreeDiet; again the symbol for re-tweet (RT) was the most prominent. Therefore, the organization knows their information is actively
shared and disseminated throughout the community because their
Twitter followers are re-tweeting the organization’s tweets.
In order to have some insights regarding the geographic locations
of the followers, we selected followers from the top 5 civic organizations in Arlington area, which had the most number of followers.
Then we visualized their location information on a map.
Fig. 10(A) shows the macro-view of the location distribution. For
example, it shows that the followers are distributed even in other
continents such as Africa and Asia. When the icons in (a) are pressed,
the visualization zooms-in and shows detail locations (Fig. 10(B)).
The purpose of these analytical and visualization tools, as noted
earlier, is to allow government and citizens to see quickly and easily
the big picture of the information and communication flows that interest them.
4.5. Analysis of Facebook Comments
Arlington County government has maintained a Facebook page
since early 2010 ( The page
had roughly 4500 fans at the end of September 2010. We analyzed
a two-month period (August 1–September 30, 2010) of posts by the
County and responses (comments) from the public by conducting a
simple content analysis by topic. There were a total of 112 posts;
the top 10 most frequent topics are shown in Fig. 11.
The most common posts by the County on the Facebook page were
about traffic (e.g., conditions, closures, metro outages), followed by
public service announcements (PSA). News (updates, and other County
announcements) and weather related posts (National Weather Service
and Arlington Weather Service advisories) were followed by various
events (biking paths, walking, music or film) in terms of frequency of
posts. There were only a few posts related to education (Arlington
Fig. 4. Number of follwers for 34 NCR civic organizations.
Fig. 5. Followers of organizations’ followers.
A.L. Kavanaugh et al. / Government Information Quarterly 29 (2012) 480–491 487
County School District) and library services (e.g., closures, speakers,
special activities) during this two-month period.
There were a total of 824 public comments to the County posts
during this two-month period. Half of the comments pertained to
about a fifth (19%) of the County posts (the top 21 posts by the County). Fig. 12 shows the distribution of the bulk of the comments on the
same top 10 County posts seen in Fig. 11.
The comments are predominantly related to traffic and miscellaneous events (that is, events that do not fall into the other ‘event’ categories shown, such as food, exercise, music, and film). Exercise
events (biking, walking) and news announcements generated the
next most frequent number of comments from the public. Almost
all the comments were highly consistent with the social media policy
of the County (e.g., no profanity or off topic comments) and were
overwhelmingly positive in tone, including many “Likes”.
Lastly, we collected videos in YouTube pertaining to Arlington,
Virginia and conducted a tag analysis of the video collection using
image software developed by IBM. We performed a search using a
Perl script and the phrase ‘Arlington County;’ this produced about
1800 videos from YouTube. We generated two types of tag clouds
using video titles and tags (see Fig. 13).
As noted earlier, a tag cloud as visualization quickly and easily represents the frequency with which different terms appear in a search
thereby providing a snapshot of what is in a large dispersed collection. The more frequently a term appears in an image collection, the
larger it appears in a tag cloud. The cloud visualization also provides
an indication of the importance of various civic issues to members
of the community. The recurring civic themes revealed in the video
analysis can be further explicated in the six categories shown in
Table 1.
A further clustering of video tags and video titles as shown in
Table 1 allows government and other users to make sense more easily
of the interests and needs of the community as expressed in the
YouTube collection at any given point.
5. Discussion and implications
The exploratory study was intended to advance technologies and
systems for social media analysis relating to both routine day-today civil life and critical incidents or emergencies. The results begin
to identify and address a combination of technical and social science
challenges. On the technical side, these include:
1) Recognizing relevant information accurately and in a timely manner,
especially from short content micro-blogging sites (e.g., Twitter); the
limited information in a tweet (i.e., less than 140 characters) makes
it difficult to identify its meaning and context which may lead to incorrect classification and misleading analysis of data;
2) Alerting government officials to the analyzed information from
multiple social media sources; due to the massive volume of the
social media data stream, it is a challenge to quickly analyze the
collected information from different sources and to make a decision based on the analysis; and
3) Visualizing the current and past status of incoming information
and the analysis of it; simple yet informative visualization design
is essential in making-sense of the data presented. We support
the sense-making process by incorporating interaction methods
with visualization to deal with large amounts of data.
On the social science side, our exploratory study results build on
social network analysis and social and political participation research
on the use of social media. We also seek to contribute to crisis informatics research and an understanding of the use of social media in
crisis situations, including more mundane crises, such as major
weather or traffic problems, and in social convergence situations,
Fig. 6. Profile biographies of Arlington UW followers.
Fig. 7. Twenty recent tweets by followers of Arlington UW.
Fig. 8. Profile biographies of CarFreeDiet.
Fig. 9. Twenty recent tweets by followers of CarFreeDiet.
488 A.L. Kavanaugh et al. / Government Information Quarterly 29 (2012) 480–491
such as crowds, rallies, and other large gatherings that are not unusual in the National Capitol Region (NCR).
We focus on Arlington and the NCR as our test case in order to analyze information, its use and impact related to local, state, national,
and international events — since it has close connections to the US
Our social media data analyses are intended to help government
and citizens of Arlington County and the NCR know how and where
to get useful information and critical communication in the event of
a crisis or social convergence condition. Our tools should help government and citizens monitor and make sense of the diversity of voices
and information that enrich the quality of life in their communities.
Tools we are developing will be available in open source for government and citizens to help them find information clustered by topic
or place and to further contribute, discuss, and interact with each
By mining content and services covering multiple media types
(i.e., text, audio, image, and video) we can develop tools to recognize
events and alert government, citizens, and community groups to see
quickly the ‘big picture’ through visualizations of social media activity
and content and changes in both over time. The intent is to enable
proactive responses, as routine problems or crises start to loom, as
events unfold, as individuals and groups respond, and as plans
(short or long-term) are made for improved services and communication. Such capabilities are relevant to a broad range of governments
throughout the US and globally. Given the efficiency of communication provided by social media, coupled with the potential to reach
many constituents quickly, governments should seek to understand
and to leverage these increasingly popular communication channels.
Governments, local organizations and citizens will continue to use a
combination of traditional communication methods (e.g., newspaper,
radio, television, magazine, telephone) and emerging tools, smart
phones and social media. Governments know they have diverse audiences with different needs and preferences. Social media are just
another set of communication channels to get word out and serve
the interests of different (mostly younger) citizens. Citizens will
continue to use different media to get and share information, not
only with each other, but with government. There is a kind of ecology of tools and devices that interplay to meet various needs for multiple purposes and types of users.
That said, however, the interplay of traditional and emerging
media may become quite blended over time. Until then, there are persistent costs (e.g., policies, legal concerns, and other issues) and benefits about which governments especially seek guidance. Typically, a
public relations person handles communication between government
and the public. But many public relations managers are not comfortable with social media. It is possible that a public relations manager
could focus on the traditional communication media such as, newsletters, press releases, and phone interviews with local TV and
radio. To manage communication with a more diverse public, however, they need someone who uses social media. So, either they have to
re-train current public relations managers, or they have the added
cost of adding another person to manage public relations activities
that involve social media.
There will continue to be legal issues concerning the interaction between traditional communication methods and social media. These include managing different ways that the public can report a problem to
authorities. Government is legally on notice of a pothole or downed
power line whether someone phones it in or tweets it. How long do
governments need to store tweets as part of the public record?
Increasingly, traditional communication technology (newspaper,
radio, television, magazine, telephone) are digital and accessible
Fig. 10. Follower locations visualized on a map. (A) Zoom-out view; (B) Zoom-in view for more detailed location information.
Fig. 11. Facebook topics Arlington County. Fig. 12. Public comments by Arlington Facebook topic.
A.L. Kavanaugh et al. / Government Information Quarterly 29 (2012) 480–491 489
online. There is a kind of asymptotic convergence — a tendency to become the same through digital form and shared network. Yet we
might want to celebrate the differences in form and function for different purposes (e.g., videos are better viewed on a larger screen).
Governments have the bad luck of living in interesting times of transition. Future research will help citizens and government to navigate
the transition from traditional methods to emerging trends. The
growing number of cities and towns that have more experience
with new media will guide others in minimizing costs and pitfalls.
The benefits, especially to citizens, in terms of greater access to information (e.g., searchable online video of meetings of interest) and
greater sharing of concerns and ideas will lead to increased awareness, collective efficacy and civic participation. The benefits to government include pro-active problem solving and positive public
relations that lead to greater political efficacy and public trust.
We are grateful for support for this research from the Virginia Tech
Center for Community Security and Resilience (CCSR) and National
Science Foundation (IIS-0916733). In addition, we thank scholarship
support from CAPES (BEX 1385/10-0). We would like to thank the government officials and representatives and the citizens of Arlington,
Virginia who participated in the six-month exploratory study.
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Andrea L. Kavanaugh, A Fulbright scholar and Cunningham Fellow, Andrea Kavanaugh
is Senior Research Scientist and Associate Director of the interdisciplinary research
Center for Human-Computer Interaction (HCI) at Virginia Tech. Her research lies in
the areas of social computing and communication behavior and effects. She has been
leading research on the use and social impact of information and communication technology funded primarily by the National Science Foundation. She is the author or editor
of three books; her research is also published in American Behavioral Scientist, Interacting with Computers, Journal for Computer Mediated Communication, Computer
Supported Cooperative Work, and The Information Society, among others. Prior to joining
the HCI Center in 2002, she served as Director of Research for the community computer
network known as the Blacksburg Electronic Village (BEV) from its inception in 1993.
She holds an MA from the Annenberg School for Communication, University of Pennsylvania, and a PhD in Environmental Design and Planning (with a focus on telecommunications) from Virginia Tech. She currently serves as Treasurer on the Board of
the Digital Government Society (DGS), and previously served on the Board of the International Telecommunications Society (2002–08).
Dr. Edward A. Fox holds a Ph.D. and M.S. in Computer Science from Cornell University,
and a B.S. from M.I.T. Since 1983 he has been at Virginia Polytechnic Institute and State
University (VPI&SU or Virginia Tech), where he serves as Professor of Computer Science.
He directs the Digital Library Research Laboratory and the Networked Digital Library of
Theses and Dissertations. He has been (co)PI on over 110 research and development projects. In addition to his courses at Virginia Tech, Dr. Fox has taught over 74 tutorials in more than 25 countries. He has given more than 63 keynote/banquet/international invited/
distinguished speaker presentations, about 154 refereed conference/workshop papers,
and over 250 additional presentations.
Fig. 13. Tag cloud of Arlington YouTube videos.
Table 1
Tag cloud categories for Arlington videos.
Law enforcement Police, cops, officer, courthouse, robbery, accident, ACPD,
Transportation Metro, street, boulevard, highway accident, parking, transit
Social issues Environment, diversity, community, city, neighborhood,
Growth, sustainability, development, bank, private, local
Political Government, elections, agencies, department
Communication Media, ABC, NBC, CBS, television, news, network, bilingual,
NoVAPJ, Spanish
490 A.L. Kavanaugh et al. / Government Information Quarterly 29 (2012) 480–491
Steven D. Sheetz is Director of the Center for Global e-Commerce and Associate Professor at the Pamplin College of Business at Virginia Tech. He received his Ph.D. in Information Systems from the University of Colorado at Boulder. His research interests
include the design and use of standards for information systems development, the diffusion of software measures, computer supported collaboration systems including
group cognitive mapping software and social networking for crisis situations, and information systems to support response to and recovery from crises. He has published
articles in Decision Support Systems, International Journal of Human-Computer Studies,
Journal of Management Information Systems, Journal of Systems and Software, and
Object-Oriented Systems. He also holds a MBA from the University of Northern Colorado
and a B.S. in Computer Science from Texas Tech University. He has substantial industry
experience in database design and OO systems development.
Seungwon Yang is a PhD student in the Department of Computer Science at Virginia
Tech, where he also received his B.S. degree. As a member of the Digital Library Research Laboratory under the supervision of his advisor Dr. Edward A. Fox, he explores
and investigates areas of topic identification, natural language processing, ontology engineering, and machine learning applied to Web archiving and social media analysis.
Other interests include a digital library curriculum development and Visual Analytics.
Currently he is working on topic identification approaches and domain ontology developments as part of his doctoral study, which has connection to his funded project the
Crisis, Tragedy, and Recovery Network. He has been participating in various multidisciplinary projects. He values the benefits of, and enjoys the synergies from those
collaborative projects.
Lin Tzy Li is a Ph.D. student in the Institute of Computing (IC) at UNICAMP, Brazil,
advised by Dr. Ricardo da S. Torres. She was a one-year PhD intern at Virginia
Tech(Digital Library Research Laboratory) under the supervision of Dr. Edward
A. Fox fromAug. 2010 to July 2011.She collaborated with the Crisis, Tragedy, and
RecoveryNetwork project team at Virginia Tech during that period. She is also a
system analystand researcher at the Telecommunication Research and Development Center (CPqD) inBrazil. Lin holds M.S. and B.S. degrees in Computer Science,
and an M.B.A degree.During her Master’s studies, Lin was involved in Bioinformatics of Brazilian GenomeResearch projects. Her current research interest includes
GIS, Database, data fusion, andintegration of image/video, text, and geographic
information retrievals. Her PhD work ison Multimodal Retrieval of Geographic
Donald J. Shoemaker holds a Ph.D from the University of Georgia. He has been at
Virginia Tech since 1974 and is currently Professor of Sociology. His primary research interests include youth violence and juvenile justice. He has extensive international research experience with youth deviance and juvenile justice,
especially in the Philippines, but also in Turkey and Sri Lanka. In 1990, he received
a Fulbright Research Scholarship to study juvenile justice in the Philippines. Recent publications include the 6th edition of Theories of Delinquency, published
by Oxford University Press and Juvenile Delinquency, published by Rowman/
Littlefield. He is currently involved with the digital library research team on the
Crisis, Tragedy, and Recovery (CTRnet ) project, funded by the National Science
Apostol (Paul) Natsev received the M.S. and Ph.D. degrees in computer science from
Duke University, Durham, NC, in 1997 and 2001, respectively. He is currently a Staff
Software Engineer and Manager in the Video Content Analysis Group at Google Research. Previously, he was a Research Staff Member at IBM Research from 2001 to
2011, and Manager of the Multimedia Research Group from 2007 to 2011. Dr. Natsev’s
research agenda is to advance the science and practice of systems that enable users to
manage and search vast repositories of unstructured multimedia content. His research
interests span the areas of image and video analysis and retrieval, computer vision, and
large-scale machine learning. Dr. Natsev is an author of more than 70 publications and
18 patents (granted or pending), and his research has been recognized with several
awards, including the 2004 Wall Street Journal Innovation Award, Multimedia category
(for the IBM MARVEL system), 2005 IBM Outstanding Technical Accomplishment
Award, 2005 ACM Multimedia Plenary Paper Award, 2006 ICME Best Poster Award,
and 2008 CIVR Public’s Choice Award (for the IBM IMARS system).
Lexing Xie received the B.S. degree from Tsinghua University, Beijing, China, in 2000,
and the M.S. and Ph.D. degrees from Columbia University, in 2002 and 2005, respectively, all in electrical engineering. Lexing Xie is Senior Lecturer in the Research School
of Computer Science at the Australian National University, she was with the IBM T.J.
Watson Research Center, Hawthorne, NY from 2005 to 2010. Her recent research interests are in multimedia mining, machine learning and social media analysis. Dr. Xie has
won several awards: the best conference paper award in IEEE SOLI 2011, the best student paper awards at JCDL 2007, ICIP 2004, ACM Multimedia 2005 and ACM Multimedia 2002. She also received the 2005 IBM Research Josef Raviv Memorial Postdoc
fellowship in computer science and engineering.
A.L. Kavanaugh et al. / Government Information Quarterly 29 (2012) 480–491 491

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We have highlighted some of the most popular subjects we handle above. Those are just a tip of the iceberg. We deal in all academic disciplines since our writers are as diverse. They have been drawn from across all disciplines, and orders are assigned to those writers believed to be the best in the field. In a nutshell, there is no task we cannot handle; all you need to do is place your order with us. As long as your instructions are clear, just trust we shall deliver irrespective of the discipline.

Are your writers competent enough to handle my paper?

Our essay writers are graduates with bachelor's, masters, Ph.D., and doctorate degrees in various subjects. The minimum requirement to be an essay writer with our essay writing service is to have a college degree. All our academic writers have a minimum of two years of academic writing. We have a stringent recruitment process to ensure that we get only the most competent essay writers in the industry. We also ensure that the writers are handsomely compensated for their value. The majority of our writers are native English speakers. As such, the fluency of language and grammar is impeccable.

What if I don’t like the paper?

There is a very low likelihood that you won’t like the paper.

Reasons being:

  • When assigning your order, we match the paper’s discipline with the writer’s field/specialization. Since all our writers are graduates, we match the paper’s subject with the field the writer studied. For instance, if it’s a nursing paper, only a nursing graduate and writer will handle it. Furthermore, all our writers have academic writing experience and top-notch research skills.
  • We have a quality assurance that reviews the paper before it gets to you. As such, we ensure that you get a paper that meets the required standard and will most definitely make the grade.

In the event that you don’t like your paper:

  • The writer will revise the paper up to your pleasing. You have unlimited revisions. You simply need to highlight what specifically you don’t like about the paper, and the writer will make the amendments. The paper will be revised until you are satisfied. Revisions are free of charge
  • We will have a different writer write the paper from scratch.
  • Last resort, if the above does not work, we will refund your money.

Will the professor find out I didn’t write the paper myself?

Not at all. All papers are written from scratch. There is no way your tutor or instructor will realize that you did not write the paper yourself. In fact, we recommend using our assignment help services for consistent results.

What if the paper is plagiarized?

We check all papers for plagiarism before we submit them. We use powerful plagiarism checking software such as SafeAssign, LopesWrite, and Turnitin. We also upload the plagiarism report so that you can review it. We understand that plagiarism is academic suicide. We would not take the risk of submitting plagiarized work and jeopardize your academic journey. Furthermore, we do not sell or use prewritten papers, and each paper is written from scratch.

When will I get my paper?

You determine when you get the paper by setting the deadline when placing the order. All papers are delivered within the deadline. We are well aware that we operate in a time-sensitive industry. As such, we have laid out strategies to ensure that the client receives the paper on time and they never miss the deadline. We understand that papers that are submitted late have some points deducted. We do not want you to miss any points due to late submission. We work on beating deadlines by huge margins in order to ensure that you have ample time to review the paper before you submit it.

Will anyone find out that I used your services?

We have a privacy and confidentiality policy that guides our work. We NEVER share any customer information with third parties. Noone will ever know that you used our assignment help services. It’s only between you and us. We are bound by our policies to protect the customer’s identity and information. All your information, such as your names, phone number, email, order information, and so on, are protected. We have robust security systems that ensure that your data is protected. Hacking our systems is close to impossible, and it has never happened.

How our Assignment  Help Service Works

1.      Place an order

You fill all the paper instructions in the order form. Make sure you include all the helpful materials so that our academic writers can deliver the perfect paper. It will also help to eliminate unnecessary revisions.

2.      Pay for the order

Proceed to pay for the paper so that it can be assigned to one of our expert academic writers. The paper subject is matched with the writer’s area of specialization.

3.      Track the progress

You communicate with the writer and know about the progress of the paper. The client can ask the writer for drafts of the paper. The client can upload extra material and include additional instructions from the lecturer. Receive a paper.

4.      Download the paper

The paper is sent to your email and uploaded to your personal account. You also get a plagiarism report attached to your paper.

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