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Obama Tweeting and Twitted: Sotomayor’s Nomination and Health Care Reform

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Having established the significance of young voters in the election of President Obama, this paper focuses on how they using micro-blogging social network site Twitter have affected the political discourse of the Obama administration centering on two of the most controversial political agendas of the Obama administration’s first 100 days – the legislation battle on health care reform and the nomination and confirmation of the first Hispanic female Supreme Court Justice, Sonia Sotomayor. This paper attempts to measure how this Obama followers react to these two politically important agendas as evidenced by their tweeting, replying, re-tweeting, and searching for further information. Despite a big difference between the total number of tweets and the amount of followers on both health care and Sotomayor nomination issues, an average of more than 1.5 million followers of President Obama’s account and around 450,000 followers of the White House account clearly shows a strong sign of engagement in the Twitter network.ed by author.
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Obama Tweeting and Twitted: Sotomayor’s Nomination and Health
Care Reform
Jongwoo Han, Ph.D.
jonghan@maxwell.syr.edu
Syracuse University
410 Crouse-Hinds Hall
Syracuse, NY 13244
Phone: (315) 443-5856
Fax: (315) 443-1075
Youngseek Kim
ykim58@syr.edu
School of Information Studies
Syracuse University
221 Hinds Hall
Syracuse, NY 13244
Phone: (315) 443-4905
DRAFT: PLEASE DO NOT CITE WITHOUT PERMISSION OF THE AUTHORS
Copyright © Jongwoo Han & Youngseek Kim
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ABSTRACT
Having established the significance of young voters in the election of President Obama,
this paper focuses on how they using micro-blogging social network site Twitter have
affected the political discourse of the Obama administration centering on two of the most
controversial political agendas of the Obama administration’s first 100 days – the
legislation battle on health care reform and the nomination and confirmation of the first
Hispanic female Supreme Court Justice, Sonia Sotomayor. This paper attempts to
measure how this Obama followers react to these two politically important agendas as
evidenced by their tweeting, replying, re-tweeting, and searching for further information.
Despite a big difference between the total number of tweets and the amount of followers
on both health care and Sotomayor nomination issues, an average of more than 1.5
million followers of President Obama’s account and around 450,000 followers of the
White House account clearly shows a strong sign of engagement in the Twitter network.
3
INTRODUCTION
The 2008 U.S. Presidential Election resulted in a great transformation and redefinition of
U.S. electoral politics as well as political landscapes throughout the world. Even though
Barack Obama was just a first-term senator at the time, his accomplishments in the 2008
Presidential election included many successes: 1) reviving the dwindling voting rate; 2)
transforming red states into blue; 3) cultivating a Blue Ocean of previously untapped
youth votes; 4) demonstrating the power of networked information technologies (NITs)
in election campaigns; 5) winning over previously anti-Democrat demographics,
including frequent churchgoers, members of the military, independents, white men,
Hispanics, and gun owners. Overall, this election saw the highest turnout rate (62.5%)
within 44 years – a total of 133 million votes – which is about 11 million more than voted
in 2004.
Despite such a sweeping victory across various demographic voting blocs, the
country remained ideologically divided. Interpreting the exit polls, Rove (2008) said
“America remains ideologically stable, with 34% of voters saying they are conservative
— unchanged from 2004. Moderates went to 44% from 45% of the electorate, while
liberals went to 22% from 21%.” Two factors seem to explain how voters can be won
across the political spectrum without ideological unification. First, the flow of votes was
temporarily redirected by the sudden collapse of the financial institutions on Wall Street
right before the election as well as public sentiment about the 5-year long war with Iraq.
Second, the Obama campaign outperformed McCain’s strategy of touting experience
over change and character.
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It was other factors, however, that played the most important role in Obama’s
success – the increased turnout and participation of the youth, which stayed strong from
the primary and caucus to the presidential campaign and the election (the longest
presidential election in U.S. history), as well as the youth’s use of digital social
networking technologies. This presidential election raised two important issues in
electoral politics and democracy: 1) an overall increase in voter turnout, especially in
young generations; and 2) the fact that their participation was initiated and maintained by
their intensive and extensive use of NITs and motivated by the post-9/11, “politics-
matter-to-me” mode of thinking (Han, 2009, 2007). Up to this point, the potential power
of youth involvement had been largely ignored, and no event of seismic proportions had
galvanized the participation of the youth. According to Keeter et al. (2008) and Han
(2009), ever since the 2000 presidential election, when voters aged 18-29 comprised the
same share of the Democratic vote (48%) as other age groups, young voters have
comprised an increasing share of the democratic vote (see Table 1). These recent data
suggest that “a significant generational shift in political allegiance is occurring” (Keeter
et al., 2008).
Table 1. Democratic Share of Presidential Vote, 1980-2008
1980 1984 1988 1992 1996 2000 2004 2008
Voters aged 18-29 44% 40% 47% 43% 53% 48% 54% 66%
All other voters 41% 40% 46% 43% 49% 48% 48% 53%
Source: Keeter et al. (2008), based on exit polls from CBS / New York Times (1980-
1988), Voter News Service (1992-2000), and National Election Pool (2004-2008).
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Table 2. Party Identification Trend
2000 2004 2008
Rep. Dem. Ind. Rep. Dem. Ind. Rep. Dem. Ind.
35% 39% 27% 37% 37% 26% 32% 39% 29%
18-29 35% 36% 29% 35% 37% 29% 26% 45% 29%
30-44 36% 38% 27% 40% 34% 26% 32% 38% 30%
45-64 33% 39% 28% 36% 37% 27% 33% 37% 29%
65+ 37% 43% 21% 39% 38% 23% 36% 39% 26%
Source: Keeter et al. (2008) based on NBC News exit polls
Tables 1 and 2 demonstrate a trend of young voters (aged 18-29) strongly
gravitating towards the Democratic Party. Han (2009) finds that the use of NITs has
contributed, in both the 2004 and 2008 presidential elections, to the formation of social
capital among the youth and, in 2008, to the election of Obama through various stages of
demonstration effects,
1
such as the 9/11 terrorist attack in 2001, the Declaration of War
on Iraq in 2003, the 2004 presidential election and the Dean phenomenon, the 2006 mid-
term election, and unprecedented primaries and caucuses in the 2008 election. This
argument raises a serious question that has been widely debated in regard to the impact of
NITs upon social capital and both electoral and general politics, especially after Obama
created a Blue Ocean with a Long Tail.
2
Having established the significance of young voters in the election of President
Obama, this paper focuses on how they using micro-blogging social network site, Twitter,
1
In the context of Korea, “demonstration effects” relate to the ways by which young generations in Korea
became aware of their potential power by using NITs, refer to Han (2007: 63-66). In regard to the
theoretical aspect of demonstration effects, please refer to Cornell & Cohn (1995) and Minkoff (1997).
2
On the concept of “Blue Ocean” and “Long Tail”, refer to the section Obama’s Long Tail.
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have affected the political discourse of the Obama administration centering on two of the
most controversial political agendas of the Obama administration’s first 100 days – the
legislation battle on health care reform and the nomination and confirmation of the first
Hispanic female Supreme Court Justice, Sonia Sotomayor. This paper attempts to
measure how Obama followers react to these two politically important agendas as
evidenced by their tweeting, replying, re-tweeting, and searching for further information.
Despite a big difference between the total number of tweets and the amount of followers
on both health care and Sotomayor nomination issues, an average of more than 1.5
million followers of President Obama’s account and around 450,000 followers of the
White House account clearly shows a strong sign of engagement in the Twitter network.
ONLINE SOCIAL NETWORKING ACTIVITIES AND ELECTORAL POLITICS
As Putnam (2000: 25-26) points out, the Golden Age of the World War II generation’s
civic-mindedness began to wane in the Baby Boomer generation, which brought about
significant changes in voting in 1965, trust in neighbors, and civic malaise. Putnam
identifies this collapse of social capital and the waning of civic-mindedness to
“generational change”, or “intercohort” change, as opposed to “individual change” (2000:
34). However, in his analysis of the capability of technology to incite generational
change, Putnam wavers: “Most social change involves both individual and generational
processes. The use of new technology, like the telephone or the Internet, illustrates this
sort of mixture. When the innovation is introduced, many people try out the new phone
or the new Web browser. As individuals change their behavior, virtually none of the
early growth in usage is attributable to generational change” (2000: 34).
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In 2000, when Putnam published Bowling Alone, it was much too early to assess
the long-term social effects of the Internet upon social connectedness and civic
engagement; however, two presidential elections have been completed since then,
accompanied by phenomenal growth in the use of the Internet and other NITs. The main
user of these NITs is the youth, who had previously been blamed for lower voting turnout
rates and the overall decline of social capital.
In the 2008 election, it was the youth who made the biggest difference. Han
(2007) argues that NITs contributed to the revitalization of the once-declining social
capital of the youth through several stages of “demonstration effects”, and he adds that
NIT use caused higher voter turnout and the formation of a cohesive voting bloc by the
youth. Highly increased usage of NITs in the context of national crises (e.g., 9/11) and
highly visible political events seems to be attributable to a generational awakening of the
“politics-matter-to-me” attitude among young voters.
This paper focuses first on how the expansion of digital social networks would
strengthen the influence of the “vital few” while not ruling out the potential of “the trivial
many” to challenge that strength in the networks and, second, on how SNS users have
affected the political discourse of the Obama administration. As John Guare’s 1990 play
“Six Degrees of Separation” aptly points out, people are more interconnected than they
realize. The convergence of digital social networks empowers those who were once
isolated – young American online users – and enhances the potential of interconnecting
them and involving them in elections and politics in general. Thus, those who are newly
connected can do something that they were never able to do before. “At the scales of tens
of millions of individuals and minute-by-minute time granularity, we can replay and
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watch the ways in which people seek out connections and form friendships on a site like
Facebook or how they coordinate with each other and engage in creative expression on
sites like Wikipedia and flickr” (Kleinberg, 2008: 66).
Before the current era of expansive networks, we perceived the world in orderly
and highly structured ways; however, now that we have become accustomed to
participating in networks regularly, we can appreciate how a few unexpected links, which
act like shortcuts through the network, open up vast opportunities to connect previously
disparate individuals. Consequently, those who are newly connected can expand their
scope of activities. There are unlimited opportunities for finding new paths and
connecting to new people because the structures and communication protocols of the
network are decentralized. The digital social network that emerges from this
phenomenon has its own structure that influences actors within the network. According
to Wetherell et al. (1994), “Social network analysis conceptualizes social structure as a
network with ties connecting members and channeling resources, focuses on the
characteristics of ties rather than on the characteristics of the individual members, and
views communities as ‘personal communities’, that is, as networks of individual relations
that people foster, maintain, and use in the course of their daily lives.” Due to the
fundamental changes in wireless and mobile communication technology, online social
network users have begun to form a seamless web of social and political connections that
link individuals to each other on personal and public issues, especially through micro-
content online social networks (MC-OSNs).
OBAMA’S LONG TAIL
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The term “long tail” was originally used in the field of statistics to indicate those portions
of a particular frequency distribution that were relatively insignificant (Patton &
Gressens,1926; Viner, 1929); later, though, when the term was applied to the field of
marketing, it was used to indicate an uninfluential majority of consumers within a given
market. For example, in their attempt to calculate a ratio representative of the public
utility industry at the time, Patton and Gressens (1926: 313) referred to a “long tail [that]
considerably increased the arithmetic labor . . . and [had little influence on] the
characteristics of the distributions.” This concept calls to mind the “Pareto Principle”,
which had been formulated earlier, in 1906, by economist Vilfredo Pareto, who observed
that 20% of the Italian population of the day – the “vital few” – owned 80% of the
national wealth, and that the remaining 80% of the population – the “trivial many” – had
little influence on the economy.
More recently, the distinction between the “vital few” and the “trivial many” has
played an important role in a wider variety of fields – such as the entertainment industry,
where executives have routinely targeted their marketing efforts towards the top 20% of
“hits” in any product line (e.g., movies, CDs, books, and DVDs) as well as the customers
who buy them. In the last ten years, however, many online businesses – including
Amazon.com, Rhapsody, and Netflix – have started to focus their marketing strategy on
the “trivial many” who constitute 80% of their total. Despite the conventional emphasis
on pleasing the powerful few, products aimed at the 80% who constitute the “trivial
many” have recently gained increasing importance in these markets; advances in
information technology have enhanced marketers’ ability to match the 80% of their
inventory that represents their less popular product lines with the 80% of their customer
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base that was formerly viewed as the “trivial many”. Amazon’s recommendation list,
which uses customers’ purchase histories to suggest additional book titles, is a good
example of how marketing targets this “long tail” that is composed of the “trivial many”.
By focusing on the needs and desires of the “trivial many”, Amazon uses its database
software to find new markets for less-popular titles, thereby increasing the influence of
this group of titles.
Commenting on the use of this marketing strategy, Anderson notes that NITs
facilitate the transformation of a largely unimportant “long tail” into a newly empowered
and highly influential “Long Tail”. Indeed, NITs have enabled the “trivial many” to gain
great influence in the market, and the outcome of this conversion process is captured in
the notion of the “Long Tail”.
3
Thus, in 2004, Anderson described the “Long Tail” as
“[those] customer demographics that buy the hard-to-find or non-hit items,” and noted
that this group’s power had increased within the market to the extent that “more than half
of Amazon’s book sales [came] from outside its top 13,000 titles” at the time. Similarly,
movies not in the top 3,000 account for 20% of Netflix’s total rentals, and the majority of
songs streamed by Rhapsody are not from its top 10,000. Due to the widespread use of
NITs, this rich but previously overlooked market, which lies beyond the reach of brick-
and-mortar retailers, has growing rapidly.
Adding onto this trend that was identified by Anderson (2004), Brynjolfsson et al.
(2006) point out that the widespread availability of information technology and Internet
3
Henceforth, this paper will use two distinct terms: ‘long tail’ (in lower case) to indicate any group of
ignored, “trivial many” in any arena; and ‘Long Tail’ (in upper case) to designate the formerly “trivial” but
newly empowered many in those areas.
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markets has lowered the cost of matching customers with products, many of which are
obscure items; they add that this new pattern has caused customers who had previously
been insignificant to increase in the market share. According to Brynjolfsson et al.,
widespread use of the Internet as a channel for retail most likely modifies the traditional
ratio to 72/28, producing a highly significant 8% shift in margin.
Having established the significance of the “Long Tail” concept within economics
and marketing, this article now applies it to the field of electoral politics in the United
States. Young voters first appeared on the radar in 2004 and now are growing in
numbers and influence; equipped with NITs and allied through off-line political activities,
they have now begun to wield substantial power in the 2008 Presidential primaries and
caucuses. Young voters, politically awakened by a series of pressing national issues,
have – through the use of the Internet, cell phones, networked public spheres (e.g., SNSs),
and MC-OSNs (e.g., Twitter) – formed a generation-specific political sense of
community and become a Long Tail, a cohesive voting power, as demonstrated by the
outcome of the 2008 Presidential election.
Even after Obama’s inauguration on January 25, 2009, this Long Tail maintained
their support and interest in the political discourse, continuing to utilize OSNs (e.g.,
Facebook, MySpace, and YouTube), as well as Short Message Services (SMSs), micro-
blogs, and MC-OSNs, (e.g., Twitter, Qik, Jaiku, and dodgeball. Micro-content online
social network sites (MC-OSNs) are short message services with a limit of 140 characters,
and they use multiple delivery channels (e.g., instant messaging, cell phones, email, the
Web) for informal real-time communication and broadcasting among friends and
strangers who voluntarily subscribe in order to maintain acquaintanceships, to receive
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and distribute valuable information, to promote certain agendas that are of interests to
particular subscribing groups, to sustain a sense of connectedness, or “to release
emotional stress” (Zhao & Rosson, 2009: 245).
DOMINANT PLAYERS OF MC-OSNs AND TWITTER
Use of MC-OSNs like Twitter have steadily increased among adult American Internet-
users, from 6% in May to 9% in November and then 11% in December, according to Pew
Internet Research (Lenhart & Fox, 2009: 3). Surprisingly, Twitter users have a median
age of 31, a bit higher than the age range chosen by the U.S. census and other studies to
represent young voters (i.e., 18 to 29); the median ages for MySpace and Facebook,
however, fall within this age range (27 and 26, respectively). Table 3 shows that the
group containing ages 25 to 34 counts for 20% of all MC-OSNs users, which is the
biggest percentage. The next largest age bracket is the youngest (i.e., 18 to 24). Overall,
MC-OSNs like Twitter comprise the dominant form of real-time communication for the
young generations. Most MC-OSNs users typically user SNSs such as Facebook,
MySpace, YouTube, and LinkedIn. SNSs users dominate this new communication
channel (23% of SNSs users are actively involved in MC-OSNs as opposed to just 4% of
non-SNSs users), which implies that their interests and important agendas in politics
would also carry through into the MC-OSNs. So who are the dominant players in these
SNSs and what is their political orientation?
Table 3. Share of MC-OSNs Users among Americans Internet Users
Age Percentage
18-24 19%
25-34 20%
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35-44 10%
45-54 5%
55-64 4%
65+ 2%
Source: Pew Internet (Lenhart & Fox, 2009: 4)
Who were these numerous young voters who had gravitated toward Obama so strongly
when he was the Democratic candidate and whose overwhelming participation in the
2008 presidential campaign proved so significant? A closer look at Obama’s Blue Ocean
(i.e., the people who constituted Obama’s Long Tail) reveals the following general
trends:
They had been through a series of test-run mobilizations (i.e., 9/11 terrorist attack
in 2001, Iraq War in 2003, 2004 Presidential election and Dean phenomenon, and
2006 mid-term elections), had changed from being politically indifferent to highly
invested in politics, and had begun to demonstrate a “politics-matter-to-me”
attitude;
They voted in greater numbers in the 2008 presidential election than in 2000 and
2004 but still recorded a lower voter turnout than any other age group; thus, they
had voting potential that could be cultivated in the future;
They had a highly mobile lifestyle, relying almost exclusively on mobile phones;
They were the most high-tech and connected national constituency in history,
sharing profiles in SNSs, engaging in entertainment activities via SNSs, using
cyberspace to network socially, and organizing with others for political events,
issues, and causes (Jones & Fox, 2009: 3, 5; Lenhart, 2009: 4, 6; Melber, 2009);
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They preferred short, simple political messages that were communicated through
personally trusted peer-to-peer communications and required no response (e.g., e-
mails and text-messages) as opposed to messages that took the more interactive
and traditional approach (e.g., landline phone calls or door-to-door canvassing)
(Youngvoterstrategies.org: 5; Dale & Strauss, 2007: 4).
During the 20
th
century, this group’s overall low turnout had been one of the most
problematic issues in American electoral politics. Young voters’ indifference to politics
was well documented by Putnam (2008), who cited a UCLA to point out that the voting
rate of college freshmen had dropped nationwide from 60% in 1966 to 28% in 2000. The
voting rate for this age group, which in 1972 had been 52%, was almost halved to 36%
by 2000.
Table 4, Reported Rates of Voting Registration and Votes Cast in 2000 and 2004
Presidential Elections (noted in thousands and in percent of total)
2000 2004 Increase
in %:
Registered
Who Voted
Ages Total #
Citizen
Total #
Registered
Total #
Voted
Total #
Citizen
Total #
Registered
Total #
Voted
18-24 23,915 12,122
(50.7 )
8,635
(36.1)
24,898 14,334
(57.6)
11,639
(46.7)
6.9 (10.6)
25-34 32,233 20,403
(63.3)
16,286
(50.5)
32,842 21,690
(66.0)
18,285
(55.7)
2.7 (5.2)
35-44 40,434 28,366
(70.2)
24,452
(60.5)
38,389 27,681
(72.1)
24,560
(64.0)
1.9 (3.5)
45-54 35,230 26,158
(74.2)
23,362
(66.3)
39,011 29,448
(75.5)
26,813
(68.7)
1.3 (2.4)
55-64 22,737 17,551
(77.2)
15,939
(70.1)
61,865 48,918
(79.1)
44,438
(71.8)
1.9 (1.7)
65-74 17,233 13,573
(78.8)
12,450
(72.2)
17,759 14,125
(79.5)
13,010
(73.3)
0.7 (1.1)
75- 14,582 11,375
(78.0)
9,702
(66.5)
15,933 12,581
(79.0)
10,915
(68.5)
1.0 (2.0)
Source: Voting and Registration in the Elections of November 2000 and 2004 (2002 and
2006 respectively), US Census Bureau.
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However, Han (2009) finds that a change of the attitude in young voters was
evident by the 2004 Presidential election, perhaps because of the 9/11 terrorist attack.
Lopez et al. (2005:2) argue that “voter turnout among young people in 2004 had surged
to its highest level in a decade,” an increase he attributed to “a close election, and high
levels of interest in the 2004 campaign” related to the post-9/11 national issues. Table 4
which displays an overview of the voter turnout for various age groups in 2000 and 2004,
illustrates that the greatest increases in both the number of registered voters (6.9%), as
well as the number of registered voters who actually voted (10.6%), occurred in voters
aged 18-24, followed by voters aged 25-34 (2.7 % and 5 %, respectively), with the
smallest increases in both categories occurring in ages 65-74 (0.7 % and 1.1 %,
respectively).
The fact that, out of all groups, the youngest shows the lowest increase in both
voter registration and voter turnout supports the major argument of this paper – that it is
the youngest voters who have the greatest potential to transform the apathetic “long tail”
into that of the vibrantly active “Long Tail.” The 2004 Presidential election exhibited an
unprecedented increase in voting – not just an overall increase of 4% for all ages but,
more importantly, an impressive proportional increase for young voters. Marcelo and
Kirby (2008) point out that, from the 2000 election to that of 2004, the percentage of
voters aged 18-29 actually increased from 14% to 16%, whereas the percentage of voters
aged 30 and older decreased from 86% to 84%.
According to Han (2007), what has really made this phenomenon unique is the
way in which young generations’ usage of SNSs in their daily lives has affected the
campaign process. One particularly important finding is that members of Generation Y
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(born between 1977 and 1990 and currently aged 18-32), also known as “Millennials”,
tend to dominate the Internet in terms of social and political networking. They use these
networks to acquire information and communicate about the election. As the most active
Internet users, they account for 26% of the total adult population and 30% of all Internet
users in the United States. The next most active group, members of Generation X (born
between 1965 and 1976 and currently aged 33-44) account for 20% of the total adult
population but comprise 23% of Internet users (Jones & Fox 2009) in the United States.
In addition to using the Internet for activities directly related to elections,
members of Generation Y also use the Internet more than other generations for
entertainment – viewing videos, playing games, blogging, downloading music and
participating in SNSs such as Facebook, MySpace, YouTube, and Twitter (Table 5). For
Generation Y, SNSs together function as a networked public sphere which is made not
“of tools, but of social production practices that these tools enable” (Benkler, 2006:219).
During the 2008 election, through the use of SNSs, “this basic model of peer production
of investigation, reportage, analysis, and communication indeed worked” (Benkler,
2006:228) and became a part of their daily Internet activities. In contrast to Generation Y,
members of older generations, such as Generation X, tend to use the Internet for
individual activities such as shopping, banking or researching health issues. The
differences between Generation Y and other generations in terms of Internet use are
summarized in Table 5 below.
Table 5, Percent of Selected Generations That Use the Internet for Various Online
Activities
Online Activity Generation Y
(18-32)
Generation X
(33-44)
Younger
Boomers
Old Boomers
(55-63)
17
(45-54)
Play games 50 38 26 28
Watch videos 72 57 49 30
Use SNSs 67 36 20 9
Download music 58 46 22 21
Create SNS
profiles
60 29 16 9
Read blogs 43 34 27 25
Create blogs 20 10 6 7
Source: excerpted from Jones and Fox (2009: 5)
This table clearly illustrates the activities that enable Generation Y to claim
cyberspace as their living space – not just by using it to take care of their individual
chores but also by using it to create a social and political community as they establish
their own rules for cyberactivism (Benkler, 2006). As older adult Internet users have
become more involved in SNSs—from just 8% in 2005 to 16% in 2006 and then 35% in
2008—their use of SNSs for political purposes has also expanded to include activities
such as discovering friends’ political interests or affiliations (29%), obtaining campaign
or candidate information (22%), signing up as a friend of a candidate (10%), and joining
a political group (9%) (Lenhart, 2009:11).
In August 2007, Barack Obama outnumbered Hilary Clinton in both MySpace
friends (169,397 vs. 133,684) and YouTube channel views (11,098,217 vs. 849,842). By
the summer of 2008, Obama could claim an amazing 750,000 active volunteers, 8,000
affinity groups, and 30,000 fundraising events (Green, 2008). According to the rankings
conducted by Twitterholic (http://twitterholic.com/), as of August 12, 2009, President
Obama ranked 7
th
in terms of the total numbers of Twitter followers but first in terms of
the total numbers of “friends” and first among politicians. For the sake of comparison,
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Hollywood star Ashton Kutcher ranked first with 3,124,506 followers and 192 friends;
the former Vice President Al Gore ranked 21
st
with 1,398,190 and 8 friends; and Senator
John McCain ranked 43
rd
with 1,145,694 and 63 friends. Although these numbers are
impressive, they represent just a portion of the long list of campaign tools used by the
Obama campaign’s Long Tail – the formerly “trivial many”. Throughout the 2008
presidential campaign, this Long Tail, which had transformed into a massive Blue Ocean
of Obama supporters, engaged in cyberactivism of the type described below:
More than a million young voters asked for campaign text messages on
their cellphones. Two million joined MyBO [(My BarackObama)], a
website fusing social networking with volunteer work, while more than 5
million supported Obama’s profile on social sites like Facebook. Most
famously, 13 million voters signed up for regular e-mails, fundraising
pitches and other communications. On election day, a staggering 25
percent of Obama voters were already directly linked to him—and one
another—through these networks. . . . During the campaign it [(the student
network)] held 19,633 grassroots events, raised more than $1.7 million
and hosted a constant stream of many-to-many communication through
more than 170,000 blog entries. (Melber, 2009: 6, 8)
The relationship between the Long Tail and digital technology is especially evident in
one Pew/Internet poll in particular (Smith & Rainie, 2008: 4, 5, 10), which summarizes
how young voters’ use of NITs is creating a new genre of political activism, as Anderson
(2004), Lopez (2005), and Brynjolfsson et al. (2006) have noted. “Political activism isn’t
just about going door-to-door anymore. It’s also about making the videos, posting on
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blogs, tying everything together, commenting, and sending text messages. All of this is a
new wave of political activism” (PBS, 2008:3). As mentioned above, Generation Y
voters, more than older voters, were found to dominate in political and electoral activities
carried out on/via SNSs. These activities fall into the following categories: posting their
own political commentary, signing up as a friend of a candidate, or starting/joining a
political group (Smith & Rainie, 2008: 10-11).
This analysis of Obama supporters during the 2008 Presidential campaign shows
the dramatic role played by voters aged 18-29 (or 32), whose dramatic transition from
disinterested/apathetic and uninfluential to strongly committed and very influential
spawned a new kind of high-tech, socially oriented politics due, in large measure, to these
voters’ social networking capacity, both online and offline. A study of the role of NITs
in the 2002 South Korean Presidential election found a similarly dramatic increase in
high-tech, socially oriented political activity by young voters – a finding discussed in
more detail in Han (2007).
Micro-content social network sites are unique in that other existing channels (e.g.,
email, phone, Instant Messaging, weblogs) cannot match their instantaneity and
convenience mainly due to the brevity of their messages and the technical compatibility
of existing digital medium in securing multiple delivery channels for MC-OSNs. Twitter,
the most popular MC-OSN, creates a user-oriented open space where any Twitter
member can subscribe to any tweet without being put through an approval process by the
information providers, whereas other SNSs (e.g., Facebook) retain both open and
exclusive membership recognition. For example, Facebook was originally designed to
share profiles among recognized and approved friends. At the same time, Facebook users
20
can open up their profiles to an indiscriminative multitude of users. Thus, the main
difference between Twitter and conventional OSNs is that Twitter is fundamentally an
open-source community available through multiple delivery channels and utilizing very
short messages. In addition, the flow and influence of information in MC-OSNs is
largely determined by the subscribers.
MC-OSNs create a cybercommunity that is mainly comprised of two groups of
people: first, those who want to maintain pre-existing relationships; and second, those
who want to share topics of interests and valuable information. In this space of tweeting,
two types of actors exist – tweet senders and tweet receivers. Because both types can
follow tweets and have followers of their own, Twitter creates a web of spiral
information-sharing patterns; furthermore, a third party can monitor the dynamics and
patterns of this information flow and measure the popularity and influence of certain
tweets. Also, MC-OSNs differ from other OSNs and Instant Messaging (IM) because the
latter two require the approval of the information-provider, whereas the former involves
no mutual recognition process.
In this community, people “achieve a level of cyber presence, being ‘out there’
and to feel another layer of connection with friends and world” (Zhao & Rosson, 2009:
243). Technically, MS-OSNs fundamentally depend upon the pervasiveness and mobility
of networked wireless information technology. Due to the seamless nature of this web of
multiple delivery channels and the open architecture, Twitter and other MC-OSNs
overcome the exclusiveness of conventional Web-based blogging and empower
indiscriminative tweet followers. Because of these technical and architectural features,
Twitter theoretically generates an opportunity of indiscriminative tweets available for
21
indiscriminative tweet followers. Therefore, it may result in the creation of
untrustworthy information; however, followers filter information by subscribing and
unsubscribing to certain tweets along the lines of their topics of interests. This filtering
process significantly enhances the level of trust and relevancy in the spiral web of
enormous amount of information sharing exchanged in the MC-OSNs. The process of
filtering information through each user’s choice of source provides more contexts to
measure the value of each tweet and the reliability of tweet providers. In the phone
interviews conducted with 11 Twitter users during September and December 2008, Zhao
and Rosson (2009: 248) found that one interviewee viewed information from Twitter as
valuable and credible due to the selective nature of MC-OSNs’ filtering functions. The
interviewee, Tasha, said “ it provides me a filter for the best types of information in the
topics that I am most interested in. Because, more often, the people I monitor in Twitter
are people who have similar interests with me, so I find them very valuable” (Zhao &
Rosson, 2009: 248).
OBAMA TWEETING AND TWEETED
Twitter.com is a real-time SMS, a kind of “what-are-you-doing-now” site, allowing users
to communicate and update each other through text-based posts of up to 140 characters in
length.
4
The Twitter Directory in 2008, and Twitterholic.com in 2009, keep statistical
information on how many people follow each member’s messages. For example, a
search on November 11, 2008 of the Twitter Directory revealed that Barack Obama’s
updates were the most followed, with 131,233 recorded as “following” and 127,294 as
4
In November 11, 2008, the total number of Twitter users was 3,183,544; Twitter’s average daily amount
of messages was 225,000; and the number of messages from BarackObama followers ranged from 6,367-
7,959 per day, 265-332 per hour, and 4.4-5.5 per minute. See, http://twitterfacts.blogspot.com/
.
22
“followers”, while 99 other identities fall far below Obama’s popularity level, reaching a
maximum of only five figures in most cases. In fact, the second is Kevin Rose with 107
“following” and 72,539 “followers”. As of August 8, 2009, the same Obama site ranked
7
th
with 1,900,945 followers and the most friends of 765,546 among listed 100 top
twitterholics, and 314 updates. This illustrates how the widespread use of the most up-to-
date digital technology can contribute to social and political networking. Not only Obama
but the Nader and Gonzalez campaign also used Twitter to update their ballot access
teams in real time. On election day, Twitter use increased 43%, Yahoo News with 55%,
Google News with 58%. Large corporations such as Cisco Systems and Jet Blue, public
institutions such as the Los Angeles Fire Department and NASA, educational institutions
such as Georgia Institute of Technology and University of Texas, and religious
institutions such as Westwinds Church in Jackson, Michigan all use Twitter to
disseminate information related to their services.
NITs are transforming the relationship between candidates and their
constituencies. The video titled “Dear Mr. Obama”, the most popular election film on
YouTube, had attracted 13 million hits by November 11 (Vaidyanathan, 2008). And as
Vaidyanathan (2008) points out, citizens using YouTube can distribute their own
messages “faster in a 15-minute news cycle than traditional media can in a 24-hour news
cycle.” These digital social networking technologies, in fact, do not decrease face-to-face
interactions but rather increase them and make them more meaningful by relating and
matching the temporal and spatial contexts of agents.
23
Diagram 1. The Life Cycle of a Tweet
Obama
(O)
Follower
1
Follower
2
Follower
N
…..
OFF
1
OFF
2
OFF
N
…..
T
1
(CT) RT
1
(CT)
Reply
1
Reply
2
RRT
1
RRT
2
Reply
1
Reply
2
Reply
1
RRT
n
OFFF
1
OFFF
2
OFFF
N
…..
White
House
(WH)
Follower
1
Follower
2
Follower
N
…..
WHFF
1
WHFF
2
WHFF
N
…..
Reply
1
Reply
2
Reply
1
Reply
2
Reply
1
WHFFF
1
WHFFF
2
WHFFF
N
…..
RRT
1
RRT
2
RRT
n
Note‐‐ T:Tweet/RT:ReTweet fortheoriginaltweet/RRT:ReTweet for thereplies/CT:ClickThroughofthe
URLincludedinatweet /OFF:FollowerofObama’s Follower/WHFF: FollowerofWhiteHouse’sFollower
Track1:Simplyreceivingthetweet
Track2:ReTweeti ng
Track3:CheckingtheURL(ClickThrough)
RT
2
(CT)
T
1
(CT) RT
1
(CT) RT
2
(CT)
T
1
(CT) RT
1
(CT) RT
2
(CT)
T
1
(CT) RT
1
(CT) RT
2
(CT)
T
1
(CT) RT
1
(CT) RT
2
(CT)
T
1
(CT) RT
1
(CT) RT
2
(CT)
Track1 Track2
Track3
Track1 Track2
Track3
24
There are three different tracks in the life cycle of a tweet. As illustrated in
Diagram 1, Obama’s tweet on health care is delivered to Obama’s followers, who can
either reply back to him or re-tweet the message onward to their own followers. At this
point, various things can happen – President Obama can re-tweet the replies from his
followers or the second loop of Obama followers (OFF in the Diagram), and their
followers can either re-tweet or reply to each other in order to discuss the issue amongst
themselves. In the life cycle of a tweet, the first track is used to simply receive and check
certain tweets. The commitment of those followers is limited to that stage of checking
the tweets they receive. This first track reveals the total volume of followers; however,
the total volume of the first track does not provide information on how many followers
actually read the tweet and how that tweet has impacted each follower.
The second track is the process of re-tweeting (RT), where the impact of a tweet
can be measured in terms of the following categories: frequency, tweet flow and transfer,
and the size of the RT nodes. In the re-tweet process, followers of certain topics are
filtered and the popularity of the topic becomes visible to general users. At this stage,
tweeters deepen their commitment not only by checking the tweets but also by
distributing the information of the original tweet sender to their followers. In this stage,
tweet distribution multiplies exponentially. This study finds that the initial stage of re-
tweeting has the most impact because the total volume of re-tweet slows down with time.
The third track includes more detailed information on topics of interests for
further references, mostly in the form of shortened URLs, due to the limitation of each
tweet to 140 characters. Bit.ly enables MC-OSNs users to shorten, share, and track links
to webpages where more substantial amounts of information are available on topics of
25
interests. Thus, the third track presents researchers with valuable data about each tweet –
how many followers checked for the second loop of substantial information over time,
what kind of follow-up conversations occurred at this final destination, and who the
visitors were. For example, a re-tweet (May 1, 2009) of an original White House tweet
on swine flu “smgFi” contains the URL http://bit.ly/smgFi
, which links to a webpage
with detailed information on swine flu. The “bit.ly” offers profiles on that specific site
through http://bit.ly/info/smgFi
with information on how many visits were made over
time, visitors’ locations, the content of conversations on this topic within this website,
and other metadata. This back-trafficking is made possible by the rules of tweeting; the
@ sign is always followed by a username, which allows users to send messages directly
to each other if they desire. For example, a message with @example would be directed at
the user named "example" although the message could still be read by anyone. Therefore,
even without specifying the return address, an author is capable of receiving replies. In
the process of exchanging tweets, third parties can also easily identify who the original
and following users are.
Twitter also has a search function that uses hashtags, words or phrases prefixed
with a #. For example, a search for "Obama" would turn up all messages that included
#Obama. A re-tweet would be expressed as “RT @Obama”. Despite the open nature of
communicating through Twitter, undisclosed messages can be exchanged exclusively
between specific Twitter users by using the “Direct Message” function. Currently, the
White House and President Obama both use the following hashtags with regards to health
care reform: #obamahealthcare, #healthcare, #healthcare09, #healthreform, #hicp, and
#hcr. In its data analysis of Twitter, this study uses an integrating interface called an
26
Application Programming Interface (API), which allows other Web services and
applications to download data from Twitter.
This study uses all three tracks to analyze how President Obama and the White
House have used Twitter and how Obama’s Long Tail has reacted to tweets since
Obama’s inauguration in 2009. By condensing many campaign catchphrases, the Obama
administration identified the three most important policy areas for reform – health care
reform, which was also suggested as a way to overcome economic depression and crisis;
the search for new green energy sources; and education. Out of these three areas, this
study focuses on health care reform since the other two policy agendas have not yet
surfaced, as well as other important political agendas, such as the nomination of Supreme
Court Justice Sonia Sotomayor. Diagram 2 introduces important milestones in the
evolution of President Obama’s nomination of Judge Sonia Sotomayor and health care
reform policy as well as critical moments that boosted tweet activity, including click
through of additional information on two issues.
On “Organizing for America”, the official website for Obama’s main reform
agendas, an “Obama Everywhere” section offers 16 channels, all of which are either
OSNs or MC-OSNs. This study focuses Obama’s use of Twitter in his efforts to share
information, to convince supporters and stakeholders, to announce campaign schedules,
to encourage dissemination of information and apply political pressure on Congressmen
in each district, and to get feedback from Twitter members. Obama has sent out a total of
52 tweets since his January 19, 2009 tweet that asked supporters “to honor Dr. Martin
Luther King Jr. by volunteering in your area.”
Method
27
This paper examines two of the most controversial political agendas of the Obama
administration’s first 100 days – the legislation battle on health care reform and the
nomination and confirmation of the first Hispanic female Supreme Court Justice, Sonia
Sotomayor. Both issues are ostensibly divided along partisan lines, which is likely to be
reflected among MC-OSNs users. Earlier in this paper, the nature and demography of
this NIT-galvanized and mostly Democratic young generation were discussed in detail.
This paper will now attempt to measure how this Obama Long Tail reacts to these two
politically important agendas as evidenced by their tweeting, replying, re-tweeting, and
searching for further information.
In order to properly identify the political reactions of the Obama Long Tail, this
paper focused on the tweets and re-tweets sent by President Obama and the White House,
the replies and re-tweets sent by followers and friends of both Obama and the White
House to each other and back to both President Obama and the White House (see
Diagram 2).
Diagram 2. Major Milestones and Twitter Timeline on Health Care Reform and Judge
Sotomayor
28
Obama’s
firsttweet
afterthe
election
1/15
White
House
opened
Twitter
account
5/1
5/21
Obama
Speechon
Guantanamo,
Energy,& HC
7/13
Judge
Sotomayor
Confirmation
Hearing
7/20
WashingPost
&ABCPollon
HC
7/21
BlueDog
meeting@
WhiteHouse
7/22
HealthCare
News
Conference
8/7
Congress
Recess&
TownHall
Meeting
Obama’s
tweetfor
HC
(45,370
visits)
6/23
5/26
Obama
nominated
Sotomayor
Obama’s
tweetfor
Sotomayor
(45,563
visits)
White
House’s
retweet of
Obama’s
717tweet
forHC
(66,357
visits)
White
House’s
tweetfor
HC
(45,369
visits)
7/29
8/6
Sotomayor
nomination
confirmed
White
House’s
tweetfor
Sotomayor
(66,358
visits)
Obama’s
tweetfor
Sotomayor’s
fr acture
(49092
visits)
6/10
EventsTimeLine
TwitterTimeLine
Obama’s
tweetfor
HC
(66,357
visits)
7/17
Note– HC:HeathCare
This research paper utilized two main data collection techniques, both of which
used the Twitter API (Application Programming Interface) functions through which
Twitter exposes its data.
5
First, this paper used the Twitter developer API to focus on
two major events of President Obama’s health care reform and nomination of Judge
Sonia Sotomayor as Supreme Court Justice. Since a third party can observe the timeline
of Twitter activity, records of all the tweets sent by President Obama (Jan. 15 – Aug. 7,
2009) and the White House (May 1 – Aug. 7, 2009) were downloaded. Tweet data was
downloaded in XML format and converted into Excel format for the further analysis; the
Excel files include the date, content, and URL of each tweet. Second, this paper also
used other Twitter Web applications which were developed through the Twitter API,
including Twitterholic.com and Twittercounter.com, to keep track of trends in data
regarding followers of both President Obama and the White House. These two websites
5
Twitter allows researchers to download only a 10-day-long amount of tweet data through API. In order to
download the data past the current week, relevant hardware including a server can deal with large amount
of data download are required.
29
provide data on the total number of followers up until 3 months ago. This paper collected
such data from April 24 to August 7, 2009.
6
Figure 1. Number of Click-throughs on URLs in Obama’s Tweet on Health Care
6/23/2009
7/17/2009
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
HealthCareClickThrough
* Source: http://bit.ly/info from January 15 to August 7, 2009
Figure 1 shows trends in the amount of “click-throughs” received by URLs that Obama
included in his tweets; these URLs redirected his followers to further references for
supplementary information on health care reform issues. This paper counted the total
number of followers who had clicked through the shortened URL using “bit.ly”
(http://bit.ly) in search of further references on health care issues. From January 15 to
August 7, 2009, a total of 54 tweets originated from Obama’s personal Twitter account.
Out of these 54 tweets, 29 were on health care reform, and all but one of which contained
URLs as shortened bit.ly-forms. Each of these 28 URLs is different from each other and
feature unique information. On the topic of Supreme Court Justice nominee Sonia
6
This paper contains data on the White House’s Twitter account from May 1, 2009, when the White House
first opened its account.
30
Sotomayor, Obama sent out four tweets. The remaining 21 tweets sent by Obama were
on diverse topics without any consistent follow-ups on specific tweets. This paper argues
that the number of “click-throughs” in this Figure 1 represents the intensity of the
reaction of Obama’s Long Tail in regard to the health care agenda; the figure represents
not only how many people use Twitter but also how many are committed to researching
health care reform further by checking out the information at the URLs where the
attached bit.ly forms take them. This sort of reactions by the Obama Long Tail of tweet
followers corresponds to the third category of tweet following actions. As shown in the
Figure 1, two major peaks indicate the occurrence of such reactions; one on June 23 with
well over 40,000 click-throughs and the other on July 17 with a little less than 70,000.
Since Twitter is an open space that discloses the contents of each tweet, this paper
was able to confirm that Obama followers reacted most intensely to the calls of President
Obama to check out the June 23 Press Conference and Obama’s speech on July 17:
“Press conference at 12:30 on energy legislation, Iran, health care and the economy.
Watch it live: http://bit.ly/duw9t (6/23/2009)” and “Speaking on health care reform.
Watch live at http://bit.ly/GOZOt #healthcare09 (7/17/2009)”. In order to find out why
these two tweets were so enthusiastically received by followers, this paper examines the
tweets that preceded and followed these two tweets and finds that all of them contained
official/factual information. Regarding the June 23 tweet, Obama sent out the following
tweets: “Organize an event for our National Health Care Day of Service on June 27 in
your community: http://bit.ly/7AEra #OFA #healthcare (6/15/2009
),” “Great news –
pharmaceuticals agree to reduce the price of prescription drugs for millions of America’s
seniors. http://bit.ly/UCkZS (6/22/2009
),” “These stories show why affordable health
31
care for every American can't wait: http://bit.ly/13Bm5M #healthcare09 PLS RT
(6/25/2009)” and “Holding online town hall on health care reform this Weds. Watch the
vid & submit your q's: http://bit.ly/U3pgV #healthcare09 (6/29/2009). Then, regarding
the July tweet responses, Obama sent out these messages: “Donate to Organizing for
America's health care campaign by 12am Thurs, and you could come to Chicago:
http://bit.ly/oBaO7 (7/15/2009),” “Spoke with members of the American Nurses
Association today on the urgent need for health care reform: http://bit.ly/tbJHj
(7/15/2009),” “Health care reform opponents scale up attacks, playing politics w/ our
lives & livelihood. Fight back: http://bit.ly/1bciXx (7/21/2009)” and “Holding primetime
news conference on health care @ 8pm tonight. Watch it live & declare your support:
http://bit.ly/17OkdA (7/22/2009).”
Figure 2. Number of Click-throughs on URLs Included in Obama’s Tweet on
Nomination of Supreme Court Justice Sonia Sotomayor
32
5/26/2009
6/10/2009
0
10,000
20,000
30,000
40,000
50,000
60,000
5/26/2009 5/31/2009 6/5/2009 6/10/2009 6/15/2009 6/20/2009 6/25/2009 6/30/2009 7/5/2009 7/10/2009
Sotomayor ClickThrough
* Source: http://bit.ly/info from January 15 to August 7, 2009
Figure 2 also shows how many followers of Obama tweets actually looked up the URLs
included in his tweet on the nomination of Sotomayor. Out of 54 tweets, 4 were about
the nominee Sotomayor, and these 4 also belong to the “third track” of tweet actions.
Compared to the topic of health care reform, which has attracted a great deal of attention
and caused great concern, Obama’s pick of Sotomayor has also generated a substantial
amount of attention – almost as much as the health care issue – especially due to the
controversy surrounding the question of her qualification for the office of a Supreme
Court Justice. As the first Hispanic female nominee, her remark comparing the
qualifications of white males to those of Hispanic females were controversial enough to
divide the public, as well as the senators in charge of the confirmation hearings, evenly.
The 32-word remark that Sotomayor made on October 26, 2001 during a speech at the
University of California, Berkeley seemed to imply that Latina women make better
33
judges than white men: "I would hope that a wise Latina woman, with the richness of her
experiences, would more often than not reach a better conclusion than a white male who
hasn't lived that life," according to the CNN report. Due to the controversial nature of her
statement, this historic nomination of the first Hispanic woman as a Supreme Court
Justice needed political support in order to secure votes from Democratic Senators and
compete against Republican Senators on the Judiciary Committee. Even though the
Obama’s tweets on the topic of Sotomayor were far fewer than those on health care
reform, the actual number of click-throughs on the urls that led to more detailed
information about Sotomayor was almost as high as the amount of click-throughs in
Obama’s tweets on health care reform (see Figure 1 and 2).
Between the beginning of the Senate hearing on July 13 and Sotomayor’s
confirmation on August 6, 2009, the crucial turning points in this case were, firstly, her
official nomination on May 26; and secondly, when she fractured her ankle on June 10,
according to Twitter data. Obama’s tweet on May 26 Video was “President Obama
announces his Supreme Court nominee: http://bit.ly/1UUPj9 (5/26/2009).” His June 10
tweet was “On Monday Supreme Court Nominee Judge Sotomayor fractured her ankle.
Sign her virtual cast: http://bit.ly/nBsg0 (6/10/2009),” which clearly represents personal
and emotional bonding between the tweeter, the followers and the person in topic.
Figure 3. Number of Click-throughs on URLs Included in the White House’s Tweet on
Health Care Reform
34
7/21/2009
7/29/2009
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
HealthCar eClickThrough
* Source: http://twitter.com/whitehouse, from May 1 to August 7, 2009
The White House sent out a total of 384 tweets from May 1 to August 7, 2009 – much
more than the 54 sent out personally by Obama. Out of 384 tweets, some 82 were about
health care reform, 26 of which had shortened-bit.ly forms of URLs attached for further
references of information on health care issues.
7
As marked in Figure 3, the tweet that
created the most click-throughs was on July 21, which this study finds very interesting
since that tweet was the same one that President Obama sent through his personal Twitter
account on July 17, as shown in Figure 1. The July 21 tweet in Figure 3 and Obama’s
personal tweet on July 17 share the address “http://bit.ly/GOZOt”, as shown in the
following tweet message: “Streaming momentarily: Obama keeps fighting on health
reform, watch live http://bit.ly/GOZOt (7/21/2009).” This fact provides significant
knowledge about the current nature of Twitter – that the most active reactions in the
7
Three were 39 tweets with URLs attached but 13 of them were overlapped.
35
Twitter are generally caused by personally and emotionally oriented messages. President
Obama’s personal charisma strongly and effectively reverberated through Twitter, which
actively engages NIT-galvanized his followers as well as individuals who comprise
Obama’s Long Tail and incited them to interact with each other.
Figure 3 provides further evidence of this finding. Another peak in this Figure
that includes data from almost 50,000 click-throughs was on July 29 when the Council of
Economic Advisors (CEA), Chair Romer, answered questions from small business
owners. According to the White House blog, President Obama, in his July 25
th
Weekly
Address, asked small business professionals to read the CEA report on how health
insurance reform would affect small businesses and to come forward with questions.
Thousands of them did, including 1,500 through the LinkedIn network alone. As
encouraged in the following tweet from the White House: “CEA Chair Romer answers
questions from small biz folks solicited by Obama. Watch/discuss/engage
http://bit.ly/tCHXt (7/29/2009)” On July 29, “CEA Chair Christina Romer sat down for a
live video chat to address some of those questions as selected by an informal board of
LinkedIn small business members.” Clearly, in the case of July 21, it was President
Obama’s request to his followers to check CEA Chair’s interview session that generated
the most click-thoroughs in the White House tweet activities.
Figure 4. Number of Click-throughs on URLs Included in the White House’s Tweet on
Sonia Sotomayor’s Nomination to Supreme Court Justice
36
8/6/2009
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
SotomayorClickThrough
* Source: http://bit.ly/info from May 1 to August 7, 2009
Among those 384 tweets that were sent out by the White House from May 1 to August 7,
2009, fifteen were related to the nomination and controversy of Sonia Sotomayor, five of
which had URLs attached for further references to this issue.
8
From May to mid-July, the
amount of those who “clicked-through” on suggested information regarding this issue
was just over 20,000. However, since July 20, Figure 4 reveals a sudden and explosive
increase in traffic checking out additional information delivered through various URLs.
The Senate confirmation hearing started on July 13 and the confirmation was on August 6,
2009. A turning point in the opposition force reached its high mark on July 21, when a
Senate panel decided to delay the vote on Sotomayor’s nomination and two key
Republican Senators made clear their opposition against Obama’s choice of Supreme
Judge nominee. This explosive trend in followers’ “click-through” activity as they search
8
There were total 7 tweets with URLs attached but 2 of them were overlapped.
37
for supplementary information seems to clearly correlate with the Republican opposition
and the needs of the White House to mobilize Obama’s Long Tail.
In comparison to President Obama’s personal Twitter account, the White House’s
tweets, as well as the reactions from their followers, provide interesting facts. The
second highest click through occurred on May 26 with the following tweet, “BTW, we
will livestream the President's announcement about his Supreme Court nominee here:
http://bit.ly/12nxRn (5/26/2009),” which again indicates the popularity and influence of
President Obama. On July 13, Judge Sotomayor made an opening statement at the Senate
hearing as announced in the following tweet: “Judge Sotomayor’s opening statement at
1:30. Tune in to any cable news network or watch it streamed: http://bit.ly/fhfXx
(7/13/2009).” The next tweet, which was in Spanish, had the lowest click-through on
record; it read, “RT @GobiernoUSA: Ahorra dinero con estos consejos para conservar
energía en el hogar: http://bit.ly/NwoJB (7/14/2009).” Then, a tweet was sent out on the
topic of Republican Senator Lugar’s comment, “Sen. Lugar (R-IN): Judge Sotomayor is
clearly qualified … a judicial temperament … I will vote to confirm http://bit.ly/DSUwL
(7/17/2009).” Followers reacted explosively to the news of the Senate confirmation of
the first Hispanic woman as Supreme Judge, as represented in the following tweet:
“History: Judge Sotomayor confirmed 68-31. Watch Obama’s response live around 3:30
http://bit.ly/GOZOt (8/6/2009).”
In order to view the popularity and influence of both President Obama’s tweets
and those of the Obama-influenced White House within the context of the total number of
“click throughs”, this paper also examined other prominent media institutions, such as
CNN, and other influential politicians, such as former Vice President Al Gore (Nobel
38
Peace Laureate) and Senator John McCain, to see how many “click throughs” their tweets
had received from May 1, 2009 to August 10, 2009. In CNN’s tweets, the most highly
clicked URL (44,474 click throughs) was “http://bit.ly/16BNY2,” which was included in
the tweet about Michael Jackson’s death on June 25, 2009. Compared to the most highly
clicked URLs in both President Obama’s and the White House’s tweets, even CNN’s
most highly clicked URL falls short by a difference of 25,000. Also, in the tweets sent
out by Al Gore and John McCain, there was only one URL with more than 10,000 click-
throughs. In conclusion, Table 6 below clearly demonstrates that the click-through
obtained by both President Obama and the White House is far higher than CNN’s highest
and Gore’s and McCain’s as well.
Table 6. Number of Click-throughs in tweets that included shortened URLs from CNN,
Al Gore and Senator John McCain
Date URL
Click-
Through Tweet
CNN
6/25
http://bit.ly/16BNY
2
44,474
Pop icon Michael Jackson is in a coma,
sources say.
6/25 http://bit.ly/AG0F3 44,419
"King of Pop" Michael Jackson has died,
according to multiple reports.
8/6 http://bit.ly/1WNEX
M
43,344
Ashton Kutcher #aplusk & Demi Moore
tweet following emergency landing at Las
Vegas airport.
6/23 http://bit.ly/q3O40 40,192
Rush-hour collision between two D.C. Metro
trains killed at least six people, Mayor
Adrian Fenty said.
7/2
http://bit.ly/Vdwdr
33,078
Video of Michael Jackson's rehearsal now
posted on CNN.com
Al Gore
6/22 http://bit.ly/WYLaC 14,039 Last chance to join me for an urgent briefing.
6/26 http://bit.ly/VfAt1 8,615
Climate debate happening on the House floor
right now. Call your member of Congress.
8/4 http://bit.ly/MgvKf 6,750
We are overjoyed by Laura and Euna's safe
return.
8/4 http://bit.ly/7CmmV 6,028 Warmest seas on record.
7/3 http://bit.ly/CCQvC 3,855 Bi-partisan Leadership and the climate crisis:
39
Source: http://bit.ly/info/ and each twitter account of CNN (twitter.com/cnnbrk), Al Gore
(twitter.com/algore), and John McCain (twitter.com/SenJohnMcCain), all from May 1 to
August 10, 2009.
Table 7 below presents a full picture of the popularity and influence of both President
Obama’s and the White House’s tweets compared to that of the most influential news
media and other top politicians in U.S. politics.
Table 7. Average Click-through for President Obama, the White House, CNN, Al Gore,
and Sen. John McCain
Barack
Obama
White House CNN Al Gore John McCain
Average
Click-
Through of
Top 5
URLs
48,835.6 50,518.8 41,101.4 7,857.4 4,297.0
Source: http://bit.ly/info/ and each twitter account of Barack Obama (twitter.com/
barackobama), White House (twitter.com/whitehouse), CNN (twitter.com/cnnbrk), Al
Gore (twitter.com/algore), and John McCain (twitter.com/SenJohnMcCain)
Figure 5. Trends in the Distribution of Re-twitted Messages
Sen. John McCain
7/10 http://bit.ly/8rJRy 6,914 A good perspective on media bias:
5/21 http://bit.ly/gqEYS 4,551
worth the click: http://bit.ly/gqEYS - All
about the pork!
6/16 http://bit.ly/8NsjF 3,641 Stars & Stripes:
5/14 http://bit.ly/16K4lh 3,536
And my mom Roberta was on The Tonight
Show with Jay Leno last night!
7/17 http://bit.ly/vdmVw 2,843
In total agreement with Secretary Gates on
the F-22:
40
0
20
40
60
80
100
120
140
160
180
1hr 2hr s 3hrs 4hr s 5hr s 6hrs 7hr s 8hr s 9hr s 10 hr s 11 hrs 12hr s 1day 2days 3days
MessageDis tributionbyRT
NumberofRT
* Source: http://twitter.com/whitehouse on August 4
This study also found this data by searching the unique URLs included in a tweet of the
White House. This tweet in particular produced the largest re-tweet. The White House
tweeted the following message on August 4 to its followers, “Don't believe everything
you see on the web about health insurance reform. Pls share: http://bit.ly/maVkF
#healthreform #hc09.” This tweet was re-Tweeted (RT) 432 times for the three days. As
the Figure illustrates, the initial RT was delivered to about 160 followers, the most out of
any RT included. Since then, except for the 7
th
hour, the number of RT deliveries reduced
dramatically over three days. A hike during the 7
th
hour is presumed to have resulted
from online activity during the free time of lunch hour. Several interpretations are
plausible from this finding. First, re-tweeting is effective for the initial stage of the first
group of specific tweet followers. Immediate Obama followers constituted the major
distribution channels in the tweet’s overall life cycle, whereas other second loops of
followers were not actively engaged in the redistribution of the tweets. Related to this
41
point, the second finding implies that, as a medium, MC-OSNs are ill-suited for long-
term dissemination of information because the information distribution structure remains
shallow and unable to overcome the first loop of the follower group. Figure 6 supports
this finding that the increasing rate of information dissemination had slowed down
significantly after the initial distribution.
Figure 6. Total Number of Re-Tweeted Messages
0
50
100
150
200
250
300
350
400
450
500
1hr 2hrs 3hr s 4hrs 5hrs 6hrs 7 hrs 8 hrs 9hrs 10hrs 11hrs 12hrs 1day 2days 3 days
TotalNumberMessageDistributionbyRT
SumofRT
*Source: http://twitter.com/whitehouse
on August 4
The dramatic dwindling of re-tweeting after the first explosive stage seems to indicate
that Twitter has not reached the level of enduring public discourse after the initial
expansion, which was spurred primarily by the personal popularity of the original tweeter.
For Twitter to act as a reliable means of public discourse, it needs to have several more
loops of re-tweeting established and overcome its reliance on personalized re-tweeting in
the initial stage.
42
Figure 7. Obama Followers, Total Tweets on Obama, and Tweets on Health Care and
Sotomayor
0
10
20
30
40
50
60
900,000
1,100,000
1,300,000
1,500,000
1,700,000
1,900,000
Followers TotalTweets HealthCare Sotomayor Linear(Followers)
5/29/2009
6/23/2009
7/20/2009
7/29/2009
6/21/2009
6/25/2009
* Source: Obama followers from http://twitterholic.com/BarackObama/, total Obama
tweets, including those on health care and Sotomayor from
http://twitter.com/barackobama
Covering the three and half months from April 24 to August 7, Figure 7 illustrates
the rise Obama’s amount of followers, the amount of their tweets on both health care
reform and Sonia Sotomayor, and the causes of the most substantial amounts of tweet
activity. In comparison to the straight line, which represents the average, the top blue
line (i.e., the amount of Obama followers) showed a modest increase from April 24 to
May 29, a modest decrease until June 26, and then a continuing increase. Thus, June 26
becomes the important watershed in the overall increase in the amount of Obama
followers. So, what triggered these changes? On June 24, the White House hosted a
Town Hall meeting on health care reform, which was broadcasted by ABC that night. On
June 27, many followers were encouraged to hold various events on health care reform in
Numberof
followers
Numberof
tweets
43
each region. This trend corresponded with the overall increase in the number of total
tweets, with the tweets on health care to a lesser degree, and with the tweets on
Sotomayor to an even lesser degree.
In regard to the agenda of health care reform, July 17 served as the most critical
moment, suddenly boosting the number of tweets. Obama’s health care reform effort
became the subject of both the usual Republican opposition and the Blue Dog democrats’
rebellion. Obama was not the first president to face stark opposition for repeatedly
claiming that federal government-initiated universal coverage reform would be an
ineffective and socialistic idea. Released on July 20, a poll conducted by The
Washington Post and ABC revealed that opposition force is gaining influence upon
constituency. The approval rating for Obama’s health care reform policy dropped from
57% to 49%, and the disapproval rating increased dramatically from 29% to 44%.
Partisan politics were clearly reflected in this change. Three-fourth of Democrats favor
the reform policy while the same ratio of Republicans opposes it. In addition, President
Obama met in the White House with representatives of the Blue Dog democrats on July
21, 2009 but without any concrete outcome. On July 22, President Obama delivered a
special news conference from the White House on the status of health care reform policy,
and all of these significant events are well reflected in Diagram 2. Ultimately, on July 30,
2009, Speaker of the House Nancy Pelosi declared war against the health care industry
and excoriated the Blue Dog democrats. The need to defend the passage of universal
health care legislation in Congress motivated President Obama, the White House, and the
Democratic leadership in the Congress to rally their supporters as well as Obama’s Long
Tail to convince others, to pressure the opposition, and to mount a massive campaign
44
during the season of Town Hall meetings as Congress entered recess on August 6. This
is what happened two months after President Obama officially proclaimed the beginning
of health care reform policy at the National Archive building on May 21, 2009.
Figure 7 clearly illustrates that health care reform is a much more important
agenda for Obama followers than the nomination and confirmation of Supreme Court
Justice Sonia Sotomayor. The followers of health care reform issues demonstrate a linear
increase almost parallel with that of the average, except in the time before and after June
25. In particular, the tweets on health care around this time increased dramatically. This
paper concludes that the sudden increase around June 25 reflects the Town Hall meeting
on health care at the White House, which was broadcasted by ABC.
Figure 8. White House Followers, Total Tweets of the White House, and Tweets on
Health Care and Sotomayor
0
50
100
150
200
250
300
350
400
0
100,000
200,000
300,000
400,000
500,000
600,000
700,000
800,000
900,000
follower s TotalTweets HealthCare Sotomayor Linear(followers)
6/27/2009
7/21/2009
7/29/2009
Numberof
followers
Numberof
tweets
45
* Source: White House followers from http://www.twittercounter.com/whitehouse,
numbers of tweets from http://twitter.com/whitehouse.
In Figure 8, the White House’s Twitter account discloses a similar pattern as the
patterrn witnessed in Obama’s personal tweet account — a major hike in tweets for
health care reform around July 20. Interestingly, the White House opened its Twitter
account on May 1, 2009. Since that time, as this Figure shows, there was a dramatic and
linear increase in both number of White House followers and the total number of tweets
about topics on the White House agenda. It also confirms that health care reform was
much more important to the followers than the nomination of Sonia Sotomayor.
On July 28, 2009, the White House sent the following tweets: “Obama AARP
tele-town hall on health care reform around 1:30, watch & chat through Facebook
http://bit.ly/tCHXt ,” “On tap: AARP tele-town hall on health care reform 1:30
(7/28/2009).” White House followers replied back to the White House, and the White
House re-tweeted (RT) next day (July 29) as follows: “Thanks @travelerbill
@DJonRoberts @monkcat @billstrong @completelydark @nbboston @TXSolutionaries
@weishin http://bit.ly/1dbXq1#hicp
(7/29/2009),” “RT @weishin: As a doctor, I won't
have to worry about patients not getting screening tests because it's not covered by
insurance. #hicp (7/29/2009),” “RT @ballookey: If the ins. companies had to play by
these rules, that would solve 95% of the problems I have right now. #hicp (7/29/2009),”
“RT @Tenness: My family's coverage doubled because of my preexisting condition.
Unacceptable. Coverage is poor despite high cost! #hicp (7/29/2009),” “RT
@sandrasalzer: These protections ensure my family won't be bankrupted because I had
cancer #hicp (7/29/2009),” “RT @mattmaggard: these h/c protections allow workers
46
more freedom 2 change jobs & start new businesses w/o fear of losing coverage #hicp
(7/29/2009),” “RT @jeremypeters: These protections will ensure I can afford, find, &
keep quality care from now (age 29) on, no matter the situation. #hicp (7/29/2009),” “RT
@GarryStetser: They matter because personal situations & health conditions change over
time, & people should not be penalized ... #hicp (7/29/2009),” and “Tell us why these 8
h/c insurance consumer protections (http://bit.ly/VidAN) matter to you & we’ll RT some
of the best #hicp (7/29/2009).” This re-tweet process clearly indicates that a cycle of
feedback has been completed between Obama and his followers through the re-tweet
process on health care reform.
In addition, this case clearly illustrates the effectiveness of MC-OSNs in
disseminating information and rallying Obama’s Long Tail through Twitter by
completing the cycle of feedback between the White House and those who tweet on the
issue of health care reform. Dr. Weishin received Obama’s request for opinions from his
supporters and replied to President Obama. In turn, President Obama re-tweeted Dr.
Weishin’s opinion to Obama’s followers. Dr. Weishin then put this exchange on his
website and informed President Obama that this exchange was available online too.
CONCLUSION
Research on Twitter contributes significantly to the scholarly attention on how NITs,
such as OSNs and MC-OSNs, affect political discourse and election campaigns because
the data itself reveals the content of the communications that are taking place through
these mediums, whereas other mediums do not disclose the content of the conversations.
For example, Han’s research on the correlation between the increased volume of mobile
phone use and the election of previous President Roh Moo-hyun in the 2002 Korean
47
Presidential election found the data incapable of indicating that the increased volume was
due to activity of those in support of electing candidate Roh in particular; it merely
indicated voting activity in general. In other words, it would be extremely difficult to
find out exactly what caused the increased use of mobile phones unless there were a
massive poll of mobile phone users at that specific time. Tweets, however, disclose their
contents and can be tracked down through replies, re-tweets, and “click-throughs” due to
the nature of Twitter’s architecture. Therefore, more research on MC-OSNs will educate
us on the impacts of NITs, such as OSNs and MC-OSNs, upon general political discourse,
politics, and electoral politics.
Also, in this research and previous studies on the relationship between NITs and
electoral politics by Han (2007, 2009), recent increases in the use of MC-OSNs are found
to be closely related with the users of conventional OSNs, such as Facebook, MySpace,
YouTube, and LinkedIn, which supports the argument of this paper that the NIT-
galvanized young generation of Obama supporters – the Long Tail that Senator Obama
cultivated and tapped into during the 2008 Presidential election – has continued their
participation in the public discourse about the major agendas of the Obama
administration’s first 100 days. Also, due to Twitter’s filtering process whereby each
individual follows certain tweets and often re-tweets these message to followers of their
own, the Twitter community appears to have a high level of trust in the reliability of the
information they share.
Overall, as illustrated by the Figures on total followers, total number of tweets,
and number of tweets on the two issues of health care and the nomination of Sotomayor,
this research finds that Twitter activates tweeters most effectively on issues that many are
48
following. Despite a big difference between the total number of tweets and the amount of
followers on both health care and Sotomayor nomination issues, an average of more than
1.5 million followers of President Obama’s account and around 450,000 followers of the
White House account clearly shows a strong sign of engagement in the Twitter network.
When tweeters reacted actively, they did so on the same issues, around June 20 and July
20, when the health care issues were at an important turning point (see Diagram 2 and
Figures 7 & 8).
This study finds that the difference between followers’ reactions to President
Obama’s personal tweets and those from the White House clearly indicates that Twitter
still significantly relies on personal charisma and popularity. Also, this paper finds, in the
case study of both Obama and the White House tweets, that similar numbers of followers
for both President Obama and the White House carefully reviewed the tweet messages
and looked for more detailed references on some important tweets, especially on health
care reform and Supreme Court Judge Sonia Sotomayor. This becomes clear when this
paper examines the numbers of “click-throughs” on URLs that were included by both
President Obama and the White House. This also indicates that Twitter users are
following the political issues of the Obama administration’s first 100 days very closely
and seeking out comprehensive information on each issue. As examined, tweeters clearly
reacted to the major events in both health care reform and the nomination of Justice
Sotomayor, which was corroborated by both Obama’s personal Tweet account and that of
the White House. By filtering a tremendous amount of tweets through an individual
subscribing process, Twitter users are looking for specific and trustworthy information
and deeply involved in the political process.
49
Nonetheless, Twitter has a long way to go before being considered a serious
public sphere – there must be several loops of re-tweeting after the initial re-tweet, and a
consistent level of re-tweets must be maintained. In other words, the volatility and the
personalization of tweet life cycle must be overcome. Because of the enormous amount
of tweet contents on these two major issues, this study did not make a serious attempt to
analyze the actual contents of the tweets. At a later stage of this research, this study finds
an effective tool for content analysis of the tweets, “WordStat and QDA (Qualitative
Data Analysis) Miner (http://www.provalisresearch.com/),” which will enable scholars to
delve into such statistical and qualitative data analysis as keyword search, words stats,
and content analysis of tweets exchanged through MC-OSNs.
50
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With the radical changes in information production that the Internet has introduced, we stand at an important moment of transition, says Yochai Benkler in this thought-provoking book. The phenomenon he describes as social production is reshaping markets, while at the same time offering new opportunities to enhance individual freedom, cultural diversity, political discourse, and justice. But these results are by no means inevitable: a systematic campaign to protect the entrenched industrial information economy of the last century threatens the promise of today's emerging networked information environment. In this comprehensive social theory of the Internet and the networked information economy, Benkler describes how patterns of information, knowledge, and cultural production are changing-and shows that the way information and knowledge are made available can either limit or enlarge the ways people can create and express themselves. He describes the range of legal and policy choices that confront us and maintains that there is much to be gained-or lost-by the decisions we make today.
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We present a framework and empirical estimates that quantify the economic impact of increased product variety made available through electronic markets. While efficiency gains from increased competition significantly enhance consumer surplus, for instance, by leading to lower average selling prices, our present research shows that increased product variety made available through electronic markets can be a significantly larger source of consumer surplus gains. One reason for increased product variety on the Internet is the ability of online retailers to catalog, recommend, and provide a large number of products for sale. For example, the number of book titles available at Amazon.com is more than 23 times larger than the number of books on the shelves of a typical Barnes & Noble superstore, and 57 times greater than the number of books stocked in a typical large independent bookstore. Our analysis indicates that the increased product variety of online bookstores enhanced consumer welfare by $731 million to $1.03 billion in the year 2000, which is between 7 and 10 times as large as the consumer welfare gain from increased competition and lower prices in this market. There may also be large welfare gains in other SKU-intensive consumer goods such as music, movies, consumer electronics, and computer software and hardware.
How the President-Elect Did It: The new voters changed the game
  • Karl Rove
Rove, Karl. 2008 November 6. "How the President-Elect Did It: The new voters changed the game." In The Wall Street Journal, Opinion.