Analyzing the Veracity of Tweets during a Major Crisis

Eugen Leitl eugen at leitl.org
Mon Dec 17 05:04:05 PST 2012


http://irevolution.net/2010/09/19/veracity-of-tweets-during-a-major-crisis/

Analyzing the Veracity of Tweets during a Major Crisis

Posted on September 19, 2010 | 16 Comments

A research team at Yahoo recently completed an empirical study (PDF) on the
behavior of Twitter users after the 8.8 magnitude earthquake in Chile. The
study was based on 4,727,524 indexed tweets, about 20% of which were replies
to other tweets. What is particularly interesting about this study is that
the team also analyzed the spread of false rumors and confirmed news that
were disseminated on Twitter.

The authors bmanually selected some relevant cases of valid news items, which
were confirmed at some point by reliable sources.b In addition, they
bmanually selected important cases of baseless rumors which emerged during
the crisis (confirmed to be false at some point).b Their goal was to
determine whether users interacted differently when faced with valid news vs
false rumors.

The study shows that about 95% of tweets related to confirmed reports
validated that information. In contrast only 0.03% of tweets denied the
validity of these true cases. Interestingly, the results also show  that bthe
number of tweets that deny information becomes much larger when the
information corresponds to a false rumor.b In fact, about 50% of tweets will
deny the validity of false reports. The table below lists the full results.

The authors conclude that bthe propagation of tweets that correspond to
rumors differs from tweets that spread news because rumors tend to be
questioned more than news by the Twitter community. Notice that this fact
suggests that the Twitter community works like a collaborative filter of
information. This result suggests also a very promising research line: it
could posible to detect rumors by using aggregate analysis on tweets.b

I think these findings are particularly important for projects like *Swift
River, which try to validate crowdsourced crisis information in real-time. I
would also be interested to see a similar study on tweets around the Haitian
earthquake to explore whether this bcollaborative filterb dynamic is an
emergent phenomena in this complex systems or simply an artifact of something
else.

Interested in learning more about binformation forensicsb? See this link and
the articles below:

    Predicting the Credibility of Disaster Tweets Automatically

    Automatically Ranking Credibility of Tweets During Major Events

    Six Degrees of Separation: Implications for Verifying Social Media

    How to Verify Crowdsourced Information from Social Media

    Truth in Age of Social Media: Social Computing & Big Data Challenge

    Truthiness as Probability: Moving Beyond the True or False Dichotomy when
Verifying Social Media

    How to Verify and Counter Rumors in Social Media

    Crowdsourcing for Human Rights Monitoring: Challenges and Opportunities
for Information Collection & Verification

    Rapidly Verifying the Credibility of Sources on Twitter

    Accelerating the Verification of Social Media Content





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