1. The document summarizes two studies on the use of Twitter as a social reporting tool during crisis events. 2. The first study examined how information authentication on Twitter during the 2010 Haiti earthquake reduced rumors and enabled collaboration. It found authentication was important to establish credibility. 3. The second study analyzed content selection on Twitter during the 2009 Gaza conflict. It introduced the concept of "second-level gatekeeping" and found an unequal distribution of content, with traditional media disproportionately represented.

1. Twitter as a Social Reporting Tool
under Crisis Events: Two Studies
K. Hazel Kwon, PhD
Culture and Communication
Drexel University

2. Organization of the Presentation
1. Presenting a preceding study “Rumor theory
and Twitter during the Haiti Earthquake
2010”: To contextualize how the main research
began
2. Presenting the main study “The second-level
gatekeeping and content concentration in
Twitter: A temporal analysis of Gaza conflict
2009”

3. 2011 Japan earthquake
& Tsunami:
•8.9
•15,844
• 5,890
•3,451
•A number of nuclear
accident
QUAKEBOOK:
•A Twitter-sourced
charity book
•Essays about the
moment of earthquake
•100% profits sent as
donation

4. “Day of Revolt 2011” in
Egypt
•2 millions at Tahrir Square
• The downfall of Murabak
•The April 6 Youth
Movement on Facebook
“We use Facebook to
schedule the protests,
Twitter to coordinate, and
YouTube to tell the world.”

5. “Ushahidi Project”
•Al-Jazeera collaborated
with Ushahidi during
Gaza-Israel conflict.
•“Networked Journalism”
• Citizens use mobile
media to report violence,
death, protest,
international aid, rape
etc.

6. What are in Common?
• Strategic communication (i.e. goal-oriented,
intend to change attitudes or behaviors or
mobilize actions).
• Communication exchanges on a global scale.
• Use mobile media and the Internet.
• Use the recent web applications (e.g. Facebook,
Twitter, Aggregating web services):
Social Media based
strategic communication

7. The preceding study: Twitter during
Haiti Earthquake 2010
• A project about the use of
social media as a social
reporting tool under
natural disasters.
• The Haiti paper looked at
the process of ambiguous
message exchanges
(rumors) developing into
strategic communication
and social collaboration.

8. The preceding study: Twitter during
Haiti Earthquake 2010
• The key finding was …
• Rumors are reduced by
adding credence to
information.
• Credible information helps
users understand the
situation correctly and
coordinate actions to solve
problems.

9. To reduce rumors…

10. To reduce rumors…
To reduce ambiguity, the
process to authenticate
information is necessary!

11. 1) Aim of the study
To understand the process of information
authentication and how it led to the emergence of
collaboration in Twitter during Haiti Earthquake.
2) Methods
• Tweets from Jan 12th to Jan 21st, 2010.
• Search hashtags (#): HaitiEarthquake, HaitiQuake,
HaitiHelp.
• Contents were categorized into three types of
statements: Ambiguous, Authenticating, and
Strategic
Haiti Earthquake 2010

12. Statement Description Examples
Ambiguous •Emotionally charged
statements
•Questions and comments
without supporting
materials
•“My soul is deeply sad”
•“Which relief agencies donate
aid to Haiti?”
•“I have no idea if it‟s true or
not”
Authenticati
ng
•Add credence to what the
user says
•Citing reputed source or
references to self /others as
an expert on something
•“CNN reporting a further 2
aftershocks in Haiti mag 5.9
and 5.5”
Strategic •Statements that suggest a
course of action
•“Please RT to help the victims
of today's earthquake!”
Statement Categories

13. Stage 1 Stage 2 Stage 3 Stage 4
Ambiguous
Authenticating
Haiti Earthquake 2010: Change of
Twitter communication over time

14. Stage 1 Stage 2 Stage 3 Stage 4
Ambiguous
Authenticating
Strategic
Haiti Earthquake 2010: Change of
Twitter communication over time

15. Stage 1 Stage 4
Pentagon: authenticating words; Triangle: strategic words
Haiti Earthquake 2010: Semantic
Network Analysis

16. Conclusions from the study…
• Information authentication is the most prominent
communication process under the crisis event.
• It‟s enacted by lending credence to what users say.
• Credence is gained by reliable sources such as links
to pictures, mainstream media, or well-known
organizations.
• In other words, by citing external contents
outside Twitter.
• Sharing external content results in re-circulating/re-
distributing existing online contents.

17. Sharing preexisting online content
• A significant part of Twitter practice, especially to use
the media for strategic communication.
• Majority previous studies assume Twitter users as
content creators rather than distributors.
• Distribution is not merely a passive consumption: the
practice is enacted based on users‟ decision making
within the established media dynamics.

18. Main Study:
A Temporal Analysis of User-Selected
Contents in Twitter during the 2009 Gaza
Conflict

19. Contributions of the study
• Theoretically…
 Introduce a concept of “second-level gatekeeping”
adapting social media environment (i.e. Twitter).
 Understand the distribution pattern of online news
contents in social media (i.e. Twitter)
• In practice…
 Strategic use of Twitter does not occur in a vacuum.
 One of the early studies to discuss the utility of social
media as a carrier of citizen engagement within the
constrains of preexisting media dynamics.

20. Traditional Model of Gatekeeping
• “The process by which selections are made in media
work, especially decisions whether or not to admit a
particular news story to pass through the „gates‟ of a
news medium” (McQuail, 1994, p.213)
• Traditional model…
- A series of filtering mechanisms within the provider‟s
system.
-The role of receiver was considered not as a part of
processing but as a final destination after the processing.
- Traditional model is not comprehensive in the user-
centric social media environment.

21. The ‘Second-level’ Gatekeeping
• The “Gated” (Barzilai-Nahon, 2008): users
intervene in gatekeeping mechanism by…
1. participating in producing new information
2. participating in circulating already existing
information
The second-level gatekeeping
Decision-making on what to select over other
alternatives: Processed news products are just one
option among all types of resources on the Web
Reconstructing information by adding the user‟s
own comment
Usually enacted by linking URL to a post

22. The ‘Second-level’ Gatekeeping
• The “Gated” (Barzilai-Nahon, 2008): users
intervene in gatekeeping mechanism by…
1. participating in producing new information
2. participating in circulating already existing
information
 the second-level gatekeeping
 decision-making on what to select over other
alternatives: processed news products are just one
option among all types of resources on the Web
 reconstructing information by adding the user‟s
own comment
usually enacted by linking URL to a post

24. Second-level Gatekeepers (SG)vs.
Opinion Leaders (OL)
• Incorporates the “two-step flow” model (Katz, 1957)
into the gatekeeping theory
• OL in two-step flow: receive information from the elite
media and influence on interpersonal networks
• Differences between OL and SG…
1) recipients of vs. participants in news production
2) influence only their social circles vs. including
unknown strangers online
3) verbal conversation vs. textual reporting (editable &
reproducible)

25. Second-level Gatekeeping in Twitter
does NOT occur in a vacuum
• Affected by the established media dynamics
(Napoli, 2008, p.57)
• Online Realm
- the semblance of openness and lowered entry
barrier.
- not ideally decentralized.
- audience attention clustered around corporatized
online services and the off-to-online presence of
traditional mass media realm.
- “Power-law” distribution

26. As diverse & decentralized as we
conveniently assume?
• Some critics against the decentralized web…
1. Sunstein (2001): Self-regulation prevents
comprehensive info. adoption.
2. Mitchelstein and Bockzkowski (2010) : No radically
different news consumption habit from offline.
3. Meraz (2009): Elite journalism and celebrity
bloggers hold he blogsophere, leading the unequal
structure, following “power-law” model.
4. Hindman (2009): Political use of the Internet shows
an unequal structure, following “power-law” model.

27. Hypotheses
H1: Twitter users‟ selection of news contents will
collectively produce a power-law
structure, representing the uneven
representation among the available content
providers.
0
20
40
60
80
100
120
140
160
180
200
0 10 20 30 40 50
P(K)=numberofproviders
ateachk
k = a frequency of being tweeted

28. Hypotheses
Why unequal structure?
Twitter‟s participatory potential is confined by…
1) The existing web infrastructure
(Hyperlink structure)
H2: The hyperlinks structure configured on the
general Web will be positively associated with
the frequency at which Twitter users select a
particular online content for redistribution.

29. Hypotheses
2) Traditional media force:
- Item diversity does not necessarily lead to exposure
diversity (Yim, 2003).
- Twitter users will be more likely to choose contents
created by traditional media realm due to their
familiarity to its format and channel royalty, and the
relative mass appeal of the high-budget products
H3: Twitter users‟ content selection will be
concentrated more to the traditional media
realm than other alternative forms of
contents.

30. Hypotheses
3) Interaction between the two?
- Mass media content may be preferred when the
website gains popularity thus is ranked on top from
the search results.
- Even though search result presents a website in a
higher-order, it may not be considered as the most
relevant if the source site were never heard
previously
H4: Twitter users‟ content selection will be
influenced by the interaction effects between
content types and hyperlinks structure.

31. Temporal Analysis
• Selection of news contents can also be
contingent on the news lifespan.
• Although a conflict is an instantaneous incident
at the moment when it breaks out, a more
complex political agenda can be unveiled as the
news is progressed.
RQ1: Is there any difference in Twitter news
selection according to the news lifespan?

32. Retweeting
• Purposive practices
• Facilitates rapid information diffusion within Twitter
• Create collective minds among the users of shared
interests
• Two types of retweeting:
(1) Retweeting external content
(2) Retweeting internally generated content : a special
case of second-level gatekeeping in Twitter

33. Retweeting
• Purposive practices
• Facilitates rapid information diffusion within Twitter
• Create collective minds among the users of shared
interests
• Two types of retweeting:
(1) Retweeting external content
(2) Retweeting internally generated content : a special
case of second-level gatekeeping in Twitter
RQ2: What types of messages are re-circulated via
retweeting among the internally generated content in
Twitter?

34. Methods
• Topic: Israel-Gaza Conflict from Dec 27, 2008 to Jan
18, 2009
- one of the representative international conflict news
- active use of social media: called „PR war”
• Data: Tweets made by personal users
- 860 first-hand tweets (only external links)
- 521 retweets (both internal content and external links)
• External sources cleaned including the top two or three
level domain names (http://www.zzz.zzz or
http://www.zzz.zzz.zzz )
• For temporal analysis: the data split into incident periods
▫ Early: Time 1 (Dec 27 – Jan 5)
▫ Late: Time 2 (Jan 6 – Jan 18)

35. Variables
• DV: a frequency of a content provider‟s website being
selected
• IVs:
(1) Content Types: Traditional media, Commercial social
media, Online journalism, Personal providers, Other org.
/institutional/community websites (Cohen‟s Kappa =
.89)
(2) Hyperlinks: In-coming hyperlinks to a particular
provider‟s website as an indicator of its popularity
(based on a global traffic)

36. Types Description Examples
Traditional Newswire, broadcasting, and print mass media.
Offline presence
Target mass audiences, wit a broad range of topics
cnn.com
aljazeera.com
guardian.co.uk
Social
Media
Commercial company providing a space for users
to easily create and share contents.
Sometimes, have an automatic aggregation
function.
youtube.com
reddit.com
facebook.com
Online
Journalism
The websites with journalistic writing style yet do
not have offline edition.
Have independent domain names.
alternet.org
huffingtonpost
allvoices.com
Personal Informal websites run by either an individual or a
small number of people.
Do not have formal organizational structure.
polizero.com
andycarvin.com
buzzsuggest.com
Others Any organizational/institutional/community
websites that were not categorized in any of above.
E.g. governmental, corporate, educational,
research, advocacy organizational websites.
gazatalk.com
un.org
arabmediasociety.
com

37. Descriptive Results
• A total of 256 unique content providers were tweeted
• The average frequency of being tweeted is 3, yet with a
huge variations, ranging from 41 times to 1 times.
• The most frequently tweeted:

38. Re-plotting after log-transformations
(Test of Power-law distribution)
Highly Selective representation: Majority of
providers (N = 176, 68.8%) selected only by a
single user (R2 = .80, p < .0001) H1 supported
-0.5
0
0.5
1
1.5
2
2.5
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8
logtransformedP(k)
log transformed k

39. H2~4: Negative Binomial Regression
Models (NBR)
•Regression model with the count DV.
•Content Type is a categorical variable, requiring a
reference level.
(1) „traditional media realm‟ was hypothesized as to be
more influential.
(2) „commercial social media‟ showed the highest mean
frequency among all.

40. Descriptive Analysis
TIME 1 TIME2
FRQ HYP N FRQ HYP N
Traditional 2.92 9.34 48 2.64 9.27 55
Social
media
3.43 10.74 28 5.75 9.30 22
On Journal 1.84 8.12 25 1.43 8.42 23
Personal 1.05 5.12 21 1.10 5.88 22
Other 1.88 6.66 33 2.47 8.21 35
Total 2.36 8.27 155 2.45 8.14 157

41. Hypotheses Testing
log(Tweet Frequency) = Intercept + b1(CT=traditional media)
+ b2(CT=online journalism) + b3(CT = personal) + b4(CT
= org/inst/community) + b5Hyperlinks + b6
(CT=traditional media)*Hyperlinks + b7CT=(online
journalism)*Hyperlinks + b8(CT=personal)*Hyperlinks
+ b9(CT=org/inst/community)*Hyperlinks.
• H2 (Hyperlinks effects): Supported on both stages
• H3 (Content Type effects): Not supported
• H4 (Interaction between Hyperlinks and Content
Type): Only supported on the later stage.

42. Model Effects
TIME 1 TIME 2
Wald df Sig. Wald df Sig.
Intercept 2.13 1 0.144 0.01 1 0.959
Hyperlinks 7.3** 1 0.007 5.09* 1 0.024
CT 2.06 4 0.725 3.79 4 0.436
CT x
Hyperlinks 3.01 4 0.556 10.49* 4 0.033
NOTE: CT = Content Types

43. Parameter Estimate for Time 2 (social
media as a reference)
B SE C.I. Wald χ2 Exp
(B)Low High
(Intercept)** -0.96 0.74 0.09 1.63 1.69 0.38
(CT =TM) 0.68 1.01 0.27 14.38 0.45 1.97
(CT =OJ) 1.26 1.01 0.49 25.58 1.56 3.53
(CT =Personal) 1.04 0.89 0.50 16.08 1.38 2.83
(CT =Other) 1.74 0.94 0.90 36.15 3.41 5.70
Hyperlinks *** 0.25 0.07 1.12 1.47 12.84 1.28
(CT =TM) x HP -0.12 0.10 0.73 1.08 1.39 0.89
(CT = OJ)x HP* -0.24 0.10 0.64 0.96 5.60 0.79
(CT = Personal) x
HP *
-0.25 0.10 0.65 0.94 6.50 0.78
(CT = other) x
HP**
-0.27 0.10 0.62 0.93 6.85 0.76

44. TIME 1 TIME 2
blue:
traditional
green:
social media
green:
social media
blue:
traditional

45. Qualitative Analysis of Retweeting
internal contents (RQ2)
• 45.1% were internally produced tweets.
• News alerts from professional news organization
(BNO: 46 times, AlGaza: 38 times)
• 134 include ordinary users‟
emotional/expressive comments:
(1) tactical information (e.g. where and how to
meet up for protest)
(2) expressive catchphrases (e.g. “War criminal
Tony Blair called the situation Gaza „hell‟”.)

46. Conclusion & Discussions (1)
• Hyperlinks from general online public influences users‟
information selection process in Twitter.
• CT becomes influential as time goes by, but only when
interacting with Hyperlinks effects: Traditional form of
contents does not necessarily guarantee the successful
„filtering-in‟.
• The popular use of commercial social media among
Twitter users: Smart adaptation of popular web
applications (i.e. aggregator website) requited for less
visible content providers (e.g. Human Rights campaign
delivered by Youtube or CNN I-Report better than by its
own website)

47. Conclusion & Discussions (2)
• As a collective outcome, user selection reveals a few
prominent information providers and a large
number of less visible providers…any implication
regarding the diversification & decentralization of
online news consumption?
• Retweeting to disseminate not only information but
also emotions and strategic actions.
• Limitations…
- no causal assessment possible
- one specific case: question about generalizability?
- English only

48. References
Barzilai-Nahon, K. (2008). Toward a theory of network gatekeeping: A framework for exploring
information control. The Journal of the American Society of Information Science and
Technology, 59(9), 1493-1512.
Katz, E. (1957). The two-step flow of communication: An up-to-date report on a hypothesis. The
Public Opinion Quarterly, 21(1), 61-78
Meraz, S. (2009). Is there an elite hold? Traditional media to social media agenda setting influence
in blog networks. Journal of Computer-Mediated Communication, 14, 682-707.
Napoli, P. M. (2008). Hyperlinking and the force of “massification.” In J. Turrow and L. Tsui
(Eds.), The Hyperlinked Society (p.56-69). Ann Arbor, MI: The University of Michigan Press.
Hindman, M. (2008). The Myth of Digital Democracy. Princeton, NJ: Princeton University Press.
McQuail, D. (1994). Mass communication theory: An introduction, 3rd ed., London, UK: Sage.
Mitchelstein, E. & Boczkowski, P. J. (2010). Online news consumption research: An assessment of
past work and an agenda for the future. New Media Society, 12, 1085-1102.
Sunstein, C. (2001). Republic.com. Princeton, NJ: Princeton University Press.
Yim, J. (2003). Audience concentration in the media: Cross-media comparisons and the
introduction of uncertainty measure. Communication Monograph, 70(2), 114-128.

49. Thanks! Any Questions? Comments?