Tag Archives: information networks

2011 Truthy Updates

WSJ video on Truthy project
Mike Conover in the WSJ's report on the Truthy project

We’re pleased to report several exciting developments in our interdisciplinary project studying information diffusion in complex online social networks. The past year has resulted in several publications. Our results on the Truthy astroturf monitoring and detection system were presented at WWW 2011 and ICWSM 2011. Research into the polarized network structure of political communication on Twitter was presented at ICWSM and received the 2011 CITASA Best Student Paper Honorable Mention. We demonstrated the feasibility of the prediction of individuals’ political affiliation from network and text data (SocialCom 2011), a machine learning application that enables large-scale instrumentation of nearly 20,000 individuals’ political behaviors, policy foci, and geospatial distribution (Journal of Information Technology and Politics). We’re also working on a paper on partisan asymmetries in online political activity surrounding the 2010 U.S. congressional midterm elections.

Our results have been widely covered in the press, including the Wall Street JournalScienceCommunications of the ACM, NPR [1,2], The Chronicle of Higher Education, Discover Magazine, The Atlantic, New ScientistMIT Technology Review, and many more.

Current and future research is supported by an award from the NSF Interface between Computer Science and Economics & Social Sciences program, and a McDonnell Foundation grant. The former will focus on building an infrastructure for the study of information diffusion in social media, the characterization of meme spread patterns, and the development of sentiment analysis tools for social media. The latter will focus on modeling efforts, especially agent-based models of information diffusion, competition for attention, and the relationship between information sharing events and social network evolution.

Truthy tool identifies smear tactics on Twitter

Astroturfers, Twitter-bombers and smear campaigners need beware this election season as a group of leading Indiana University information and computer scientists today unleashed Truthy.indiana.edu, a sophisticated new Twitter-based research tool that combines data mining, social network analysis and crowdsourcing to uncover deceptive tactics and misinformation leading up to the Nov. 2 elections. Combing through thousands of tweets per hour in search of political keywords, the team based out of IU’s School of Informatics and Computing will isolate patterns of interest and then insert those memes (ideas or patterns passed by imitation) into Twitter’s application programming interface (API) to obtain more information about the meme’s history.

In the run-up to the mid-term elections, Truthy uncovered a number of abuses such as robot-driven traffic to politician websites and networks of bot accounts controlled by individuals to promote fake news. These findings have been widely covered in the press, with mentions in The Atlantic, MIT Technology Review, PC World, New Scientist, NPR, Ars Technica, Fast Company, The Chronicle of Higher Education, The New York Times Magazine, and many other media. Read more here and here.

Hypertext 2009

ht09Fil Menczer is one of the organizers of Hypertext 2009, the 20th ACM Conference on Hypertext an Hypermedia. The conference will be held June 29-July 1 at the Villa Gualino Convention Centre, on the hills overlooking Torino, Italy. Hypertext is the main venue for high quality peer-reviewed research on “linking.” The Web, the Semantic Web, the Web 2.0, and Social Networks are all manifestations of the success of the link. With a 70% increase in submissions, Hypertext 2009 will have a strong and diverse technical program covering all research concerning links: their semantics, their presentation, the applications, as well as the knowledge that can be derived from their analysis and their effects on society. The conference will also feature demos, posters, a student research competition, four workshops, and keynotes by Lada Adamic and Ricardo Baeza-Yates.

NaN

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Networks & agents Network

NaN is a research group exploring the modeling, simulation, and analysis of complex social and information networks, adaptive agents, and social computing systems. We especially focus on social media and the Web as complex techno-social networks in which we leave abundant traces of our activities: what we do, what we are interested in, whom we talk to, what knowledge we acquire and contribute. Our research spans from modeling the dynamic processes that occur online (how information networks grow and evolve, how individual and collective traffic patterns emerge, how attention bursts are generated and shaped by social and search tools) to designing tools that mine the Web to build better search, navigation, management, and recommendation tools (where ‘better’ means more intelligent, autonomous, robust, personalized, contextual, scalable, adaptive, and so on). We have ongoing collaborations with colleagues at the ISI Foundation, Yahoo Labs, and MoBS Lab.

Active NaN projects

Search Bias
Bias
Information Diffusion
Information Diffusion
Kinsey Reporter
Kinsey Reporter
DESPIC
DESPIC
Information Diffusion
Meme Diffusion
Scholarometer
Scholarometer
Web Dynamics
Web Dynamics
Web Traffic Analysis & Modeling
Web Traffic
Web Security
Web Security

Archived NaN projects

GiveALink
GiveALink
Text & Link Modeling
Text & Link Modeling
Sixearch
Sixearch
Network Flow Analysis
Network Flow Analysis
WebGraph++
WebGraph++
InfoSpiders
InfoSpiders
Web Topologies
Web Topologies
IntelliShopper
IntelliShopper
ELSA
ELSA
LEE
LEE
BioNets
BioNets
ACE
ACE

Growing And Navigating The Small World Web By Local Content

A PNAS paper on Growing And Navigating The Small World Web By Local Content was announced in press releases by PNAS News and UIowa. A radio interview for the program Science in Action was broadcast by BBC World Service (QuickTime | Flash | MP3). The paper received coverage in Technology Research News, ACM TechNews, Complexity Digest, Insight, @-web, Ascribe, Boston.com, E4, ResearchBuzz