I was honored to give a keynote presentation at PLEAD 2012, the CIKM Workshop on Politics, Elections and Data. My talk was titled The diffusion of political memes in social media. The workshop was held in beautiful Maui Hawaii, but alas, I could not attend in person and gave the presentation remotely via skype 🙁
Research by our Truthy team was recently featured in New Scientist, USA Today, and the cover story of Science News. The Truthy project, developed by CNetS researchers and doctoral students, aims to study the factors affecting the spread of information — and misinformation — in social media.
The Truthy site charts tweet sentiment and volume related to themes such as social movements and news. It also monitors Twitter activity to build interactive networks that let visitors visualize the diffusion networks of memes, identify the most influential information spreaders, and explore those influential feeds and other information about their online activity, such as sentiment and language. Other tools let you map the geo-temporal diffusion of memes, generate YouTube movies that display how hashtags emerge and connect, and download data directly from Twitter. With these analytics, one can begin to ask question such as: How does sentiment change in response to events and memes? What memes survive over time? Who are the most influential users on a particular topic?
For more press coverage go to the Truthy press page.
University and industry scientists are determining how to forecast significant societal events, ranging from violent protests to nationwide credit-rate crashes, by analyzing the billions of pieces of information in the ocean of public communications, such as tweets, web queries, oil prices, and daily stock market activity.
“We are automating the generation of alerts, so that intelligence analysts can focus on interpreting the discoveries rather than on the mechanics of integrating information,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering in the computer science department at Virginia Tech. He is leading the team of computer scientists and subject-matter experts from Virginia Tech, the University of Maryland, Cornell University, Children’s Hospital of Boston, San Diego State University, University of California at San Diego, and Indiana University, and from the companies, CACI International Inc., and Basis Technology.
CNetS Professors Bollen and Rocha from the School of Informatics and Computing at Indiana University are members of this project. Prof. Bollen, has devised a way to evaluate the tone of tweets – calm, alert, vital, etc. — to predict stock market trends. Prof. Rocha, has developed bio-inspired methods to predict associations in biochemical, social, and knowledge networks, including web and e-mail systems.
Additional details: Researchers study new ways to forecast critical societal events.
In our paper on Competition among memes in a world with limited attention in Nature Scientific Reports, Lilian Weng and coauthors Sandro Flammini, Alex Vespignani, and Fil Menczer report that we can explain the massive heterogeneity in the popularity and persistence of memes as deriving from a combination of the competition for our limited attention and the structure of the social network, without the need to assume different intrinsic values among ideas. The findings have been mentioned in the popular press, including Information Week, The Atlantic, and the Dutch daily NRC.
Prof. Flammini (PI) and Menczer have been awarded a three-year, $2M grant from DARPA in the context of the Social Media in Strategic Communication (SMISC) program, whose primary goal is “to develop a new science of social networks built on an emerging technology base,” Our IU unit leads a three-group team that includes collaborators at Lockheed-Martin Advanced Technology Lab and the University of Michigan. The funded project is aimed at designing and implementing a system to detect online persuasion campaigns.
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 Journal, Science, Communications of the ACM, NPR [1,2], The Chronicle of Higher Education, Discover Magazine, The Atlantic, New Scientist, MIT 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.
The Center for Complex Networks and Systems Research has an open postdoctoral position to study how ideas propagate through complex online social networks. The position is funded by a McDonnell Foundation’s grant in Complex Systems. The appointment starts in January 2012 for one year and is renewable for up to 3 additional years. The salary is competitive and benefits are generous.
The postdoc will join a dynamic and interdisciplinary team that includes computer, physical, and cognitive scientists. The postdoc will work with PIs Filippo Menczer and Alessandro Flammini and several PhD students on analysis and modeling of social media data. Areas of focus will include information diffusion patterns, epidemic models for the spread of ideas, interactions between network traffic and structure dynamics, and agent-based models to explain the emergence of viral bursts of attention. Domains of study will include politics, scientific knowledge, and world events. Go to the grant page or project page for further details on the team and project.
The ideal candidate will have a PhD in computing or physical sciences; a strong background in analysis and modeling of complex systems and networks; and solid programming skills necessary to handle big data and develop large scale simulations.
To apply, email/send a CV and names and emails of three references to Tara Holbrook. Applications received by Oct. 24, 2011 will be given full consideration, but the position will remain open until a successful candidate is identified.
Indiana University is an Equal Opportunity/Affirmative Action employer. Applications from women and minorities are strongly encouraged. IU Bloomington is vitally interested in the needs of Dual Career couples.
Scholarometer is becoming a more mature tool. The idea behind scholarometer — crowdsourcing scholarly data — was presented at the Web Science 2010 Conference in Raleigh, North Carolina, along with some promising preliminary results. Recently acquired functionality includes a Chrome version, percentile calculations for all impact measures, export of bibliographic data in various standard formats, heuristics to determine reliable tags and detect ambiguous names, etc. Next up: an API to share annotation and impact data, and an interactive visualization for the interdisciplinary network.
The IEEE Spectrum piece Real-Time Search Stumbles Out of the Gate discusses the recent integration of real-time search features, such as Twitter and other microblog entries, into major search engines. Professor Filippo Menczer, CNetS associate director, comments in the article on the challenges posed by real-time search. Here is an excerpt of the interview:
IU’s Menczer suggests that with all this user-generated content, the environment is more complex than the one Google’s PageRank algorithm had to deal with. While search used to be about relationships between pages, he explains, now it’s about relationships between ”people, tags, Web pages, ratings, votes, and direct social links….It may not be that page A points to page B but rather that user John follows Mary and replies to the tweet of Jane and retweets it.” That makes it ”a more complicated ecosystem,” he says, ”but a very rich one,” and search engines will need ”more sophisticated ways to extract data from these relationships” […]