Detecting and Tracking Political Abuse in Social Media
Proceedings of the International AAAI Conference on Web and Social MediaPublished 3 August 2021Open access
A. Ratkiewicz, Michael Conover, Mark Meiss, Bruno Gonçalves, Alessandro Flammini, Filippo Menczer
Citations586
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
A machine learning framework that combines topological, content-based and crowdsourced features of information diffusion networks on Twitter to detect the early stages of viral spreading of political misinformation.
Abstract
We study astroturf political campaigns on microblogging platforms: politically-motivated individuals and organizations that use multiple centrally-controlled accounts to create the appearance of widespread support for a candidate or opinion. We describe a machine learning framework that combines topological, content-based and crowdsourced features of information diffusion networks on Twitter to detect the early stages of viral spreading of political misinformation. We present promising preliminary results with better than 96% accuracy in the detection of astroturf content in the run-up to the 2010 U.S. midterm elections.
Keywords
Social SciencesComputer Science
ACM SIGKDD Explorations NewsletterThe WEKA data mining software
17,849 Citations2009Mark Hall, Eibe Frank +4 more
This paper provides an introduction to the WEKA workbench, reviews the history of the project, and, in light of the recent 3.6 stable release, briefly discusses what has been added since the last stable version (Weka 3.4) released in 2003.
What is Twitter, a social network or a news media?
6,692 Citations2010Haewoon Kwak, Changhyun Lee +2 more
This work is the first quantitative study on the entire Twittersphere and information diffusion on it and finds a non-power-law follower distribution, a short effective diameter, and low reciprocity, which all mark a deviation from known characteristics of human social networks.
Journal of Computational ScienceTwitter mood predicts the stock market
4,995 Citations2011Johan Bollen, Huina Mao +1 more
This work investigates whether measurements of collective mood states derived from large-scale Twitter feeds are correlated to the value of the Dow Jones Industrial Average (DJIA) over time and indicates that the accuracy of DJIA predictions can be significantly improved by the inclusion of specific public mood dimensions but not others.
Reviews of Modern PhysicsStatistical physics of social dynamics
4,025 Citations2009Claudio Castellano, Santo Fortunato +1 more
Earthquake shakes Twitter users
3,667 Citations2010Takeshi Sakaki, Makoto Okazaki +1 more
This paper investigates the real-time interaction of events such as earthquakes in Twitter and proposes an algorithm to monitor tweets and to detect a target event and produces a probabilistic spatiotemporal model for the target event that can find the center and the trajectory of the event location.
Cambridge University Press eBooksDynamical Processes on Complex Networks
2,724 Citations2008Alain Barrat, Marc Barthélemy +1 more
A new and recent account presents a comprehensive explanation of the effect of complex connectivity patterns on dynamical phenomena in a vast number of everyday systems that can be represented as large complex networks.
Proceedings of the International AAAI Conference on Web and Social MediaPredicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment
2,681 Citations2010Andranik Tumasjan, Timm O. Sprenger +2 more
It is found that the mere number of messages mentioning a party reflects the election result, and joint mentions of two parties are in line with real world political ties and coalitions.
Why we twitter
2,639 Citations2007Akshay Java, Xiaodan Song +2 more
It is found that people use microblogging to talk about their daily activities and to seek or share information and the user intentions associated at a community level are analyzed to show how users with similar intentions connect with each other.
The political blogosphere and the 2004 U.S. election
2,605 Citations2005Lada A. Adamic, Natalie Glance
Differences in the behavior of liberal and conservative blogs are found, with conservative blogs linking to each other more frequently and in a denser pattern.
ACM Transactions on the WebThe dynamics of viral marketing
2,069 Citations2007Jure Leskovec, Lada A. Adamic +1 more
Predicting the Future with Social Media
2,064 Citations2010Sitaram Asur, Bernardo A. Huberman
Journal of the American Society for Information Science and TechnologyTwitter power: Tweets as electronic word of mouth
1,644 Citations2009Bernard J. Jansen, Mimi Zhang +2 more
Meme-tracking and the dynamics of the news cycle
1,547 Citations2009Jure Leskovec, Lars Bäckström +1 more
This work develops a framework for tracking short, distinctive phrases that travel relatively intact through on-line text; developing scalable algorithms for clustering textual variants of such phrases, and identifies a broad class of memes that exhibit wide spread and rich variation on a daily basis.
Mining concept-drifting data streams using ensemble classifiers
1,254 Citations2003Haixun Wang, Wei Fan +2 more
This paper proposes a general framework for mining concept-drifting data streams using weighted ensemble classifiers, and shows that the proposed methods have substantial advantage over single-classifier approaches in prediction accuracy, and the ensemble framework is effective for a variety of classification models.
Sampling from large graphs
1,192 Citations2006Jure Leskovec, Christos Faloutsos
The best performing methods are the ones based on random-walks and "forest fire"; they match very accurately both static as well as evolutionary graph patterns, with sample sizes down to about 15% of the original graph.
Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network
1,179 Citations2010Bongwon Suh, Lichan Hong +2 more
It is found that, amongst content features, URLs and hashtags have strong relationships with retweetability and the number of followers and followees as well as the age of the account seem to affect retweetability, while, interestingly, thenumber of past tweets does not predict retweetability of a user's tweet.
Communications of the ACMSocial phishing
1,116 Citations2007Tom N. Jagatic, Nathaniel A. Johnson +2 more
Sometimes a "friendly" email message tempts recipients to reveal more online than they otherwise would, playing right into the sender's hand.
Beyond Microblogging: Conversation and Collaboration via Twitter
956 Citations2009C. Honey, Susan C. Herring
A corpus of naturally-occurring public Twitter messages reveals a surprising degree of conversationality, facilitated especially by the use of @ as a marker of addressivity, and shed light on the limitations of Twitter's current design for collaborative use.
Twitter under crisis
943 Citations2010Marcelo Mendoza, Bárbara Poblete +1 more
The behavior of Twitter users under an emergency situation is explored and it is shown that it is posible to detect rumors by using aggregate analysis on tweets, and that the propagation of tweets that correspond to rumors differs from tweets that spread news.
First MondaySocial networks that matter: Twitter under the microscope
940 Citations2008Bernardo A. Huberman, Daniel M. Romero +1 more
Inferring networks of diffusion and influence
684 Citations2010Manuel Gomez-Rodriguez, Jure Leskovec +1 more
This work develops an efficient approximation algorithm that scales to large datasets and in practice gives provably near-optimal performance and identifies the optimal network that best explains the observed infection times.
TwitterStand
669 Citations2009Jagan Sankaranarayanan, Hanan Samet +3 more
This work investigates the use of Twitter to build a news processing system, called TwitterStand, from Twitter tweets, to capture tweets that correspond to late breaking news, analogous to a distributed news wire service.
@spam
558 Citations2010Chris Grier, Kurt Thomas +2 more
A characterization of spam on Twitter finds that 8% of 25 million URLs posted to the site point to phishing, malware, and scams listed on popular blacklists, and examines whether the use of URL blacklists would help to significantly stem the spread of Twitter spam.
Vizster: Visualizing Online Social Networks
546 Citations2006Jeffrey Heer, danah boyd
This work has designed and implemented a visualization system for playful end-user exploration and navigation of large scale online social networks, and builds upon familiar node link network layouts to contribute customized techniques for exploring connectivity in large graph structures.
Who is tweeting on Twitter
503 Citations2010Zi Chu, Steven Gianvecchio +2 more
This paper proposes a classification system that uses the combination of features extracted from an unknown user to determine the likelihood of being a human, bot or cyborg on Twitter and demonstrates the efficacy of the proposed classification system.
Characterizing debate performance via aggregated twitter sentiment
473 Citations2010Nicholas Diakopoulos, David A. Shamma
An analytical methodology and visual representations are developed that could help a journalist or public affairs person better understand the temporal dynamics of sentiment in reaction to the debate video.
Mining concept-drifting data streams using ensemble classifiers
395 Citations2003Haixun Wang, Wei Fan +2 more
Conversational tagging in twitter
311 Citations2010Jeff Huang, Katherine Thornton +1 more
The micro-meme phenomenon is described and the importance of this new tagging practice for the larger real-time search context is discussed: emergent topics for which a tag is created, used widely for a few days, then disappears.
Outtweeting the twitterers - predicting information cascades in microblogs
247 Citations2010Wojciech Galuba, Karl Aberer +3 more
A propagation model is proposed that predicts which users are likely to mention which URLs in the social network of Twitter, a popular microblogging site, and correctly accounts for more than half of the URL mentions in the data set.
arXiv (Cornell University)Inferring Networks of Diffusion and Influence
235 Citations2010Manuel Gomez-Rodriguez, Jure Leskovec +1 more
Wellesley College Digital RepositoryWellesley (Wellesley College)From Obscurity to Prominence in Minutes: Political Speech and Real-Time Search
139 Citations2010Eni Mustafaraj, Panagiotis Metaxas
It is argued that in the context of political speech, real-time search results provides disproportionate exposure to personal opinions, fabricated content, unverified events, lies and misrepresentations that would otherwise not find their way in the first page, giving them the opportunity to spread virally.
SSRN Electronic JournalInfluence and Passivity in Social Media
71 Citations2010Daniel M. Romero, Wojciech Galuba +2 more
An algorithm is proposed that determines the influence and passivity of users based on their information forwarding activity and it is demonstrated that high popularity does not necessarily imply high influence and vice-versa.
Determining the public mood state by analysis of microblogging posts
37 Citations2010Johan Bollen
It is argued that sentiment analysis of minute text corpora (such as tweets) is efficiently obained via a syntactic, term-based approach that requires no training or machine learning and stressed the importance of measuring mood and emotion using well-established instruments rooted in decades of empirical psychometric research.