2,012 research outputs found
Detecting and Tracking the Spread of Astroturf Memes in Microblog Streams
Online social media are complementing and in some cases replacing
person-to-person social interaction and redefining the diffusion of
information. In particular, microblogs have become crucial grounds on which
public relations, marketing, and political battles are fought. We introduce an
extensible framework that will enable the real-time analysis of meme diffusion
in social media by mining, visualizing, mapping, classifying, and modeling
massive streams of public microblogging events. We describe a Web service that
leverages this framework to track political memes in Twitter and help detect
astroturfing, smear campaigns, and other misinformation in the context of U.S.
political elections. We present some cases of abusive behaviors uncovered by
our service. Finally, we discuss promising preliminary results on the detection
of suspicious memes via supervised learning based on features extracted from
the topology of the diffusion networks, sentiment analysis, and crowdsourced
annotations
De retibus socialibus et legibus momenti
Online Social Networks (OSNs) are a cutting edge topic. Almost everybody
--users, marketers, brands, companies, and researchers-- is approaching OSNs to
better understand them and take advantage of their benefits. Maybe one of the
key concepts underlying OSNs is that of influence which is highly related,
although not entirely identical, to those of popularity and centrality.
Influence is, according to Merriam-Webster, "the capacity of causing an effect
in indirect or intangible ways". Hence, in the context of OSNs, it has been
proposed to analyze the clicks received by promoted URLs in order to check for
any positive correlation between the number of visits and different "influence"
scores. Such an evaluation methodology is used in this paper to compare a
number of those techniques with a new method firstly described here. That new
method is a simple and rather elegant solution which tackles with influence in
OSNs by applying a physical metaphor.Comment: Changes made for third revision: Brief description of the dataset
employed added to Introduction. Minor changes to the description of
preparation of the bit.ly datasets. Minor changes to the captions of Tables 1
and 3. Brief addition in the Conclusions section (future line of work added).
Added references 16 and 18. Some typos and grammar polishe
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