Thanks to support from the Indiana University Network Science Institute (IUNI), the full content of the Twitter data repository from the Observatory on Social Media (OSoMe) is now available to all IU researchers. Many tools to detect social bots, study the spread of fake news, visualize meme diffusion networks, trends, and maps, as well as APIs to access this data, have been available to the general public since mid-2016. Now, however, the IU research community can access enhanced data and content from the large collection, based on a 10% sample of all public tweets. A dedicated portal allows IU faculty and students to submit queries to the OSoMe cluster based on hashtags, URLs, keywords, geo-coordinates, and other criteria. At any time the system can search and retrieve data from the previous 18 months. We hope this resource will spur and support new research projects in all areas of computing, natural, and social sciences.
The Center for Complex Networks and Systems Research (cnets.indiana.edu) at Indiana University, Bloomington has an open postdoctoral position to study how information spreads through complex online social networks. The position funded by the DARPA program on Computational Simulation of Online Social Behavior (SocialSim). The anticipated start date for this position is January 1, 2018 (negotiable). This is an annual renewable appointment for up to 3 years subject to performance and funding. Continue reading Postdoctoral Fellowship: Simulation of Information Diffusion in Online Social Networks
A project from NaN and IUNI was among 20 selected (out of over 800 applications) to address the spread of misinformation with support from the Knight Prototype Fund. Led by Fil Menczer, Giovanni Ciampaglia, Alessandro Flammini and Val Pentchev, the project will integrate the Hoaxy and Botometer tools and uncover attempts to use Internet bots to boost the spread of misinformation and shape public opinion. The tool aims to reveal how this information is generated and broadcasted, how it becomes viral, its overall reach, and how it competes with accurate information for placement on user feeds. The project will be supported by the Democracy Fund, which in March, along with partners Knight Foundation and Rita Allen Foundation, launched an open call for ideas around the question: How might we improve the flow of accurate information? The call sought projects that could be quickly built to respond to the challenges affecting the health of our news ecosystem and ultimately our democracy. The winning projects will receive a share of $1 million through the Knight Prototype Fund, a program focused on human-centered approaches to solving difficult problems.
If you get your news from social media, as most Americans do, you are exposed to a daily dose of hoaxes, rumors, conspiracy theories and misleading news. When it’s all mixed in with reliable information from honest sources, the truth can be very hard to discern.
Among the millions of real people tweeting about the presidential race, there are also a lot accounts operated by fake people, or “bots.” Politicians and regular users alike use these accounts to increase their follower bases and push messages. PBS NewsHour science correspondent Miles O’Brien reports on how CNetS computer scientists can analyze Twitter handles to determine whether or not they are bots.
Research on detection of social bots by CNetS faculty members Alessandro Flammini and Filippo Menczer, former IUNI research scientist Emilio Ferrara, and graduate students Clayton Davis, Onur Varol, and Prashant Shiralkar was featured on the covers of the two top computing venues: the June issue of Computer (flagship magazine of the IEEE Computer Society) and the July issue of Communications of the ACM (flagship publication of the ACM). Continue reading Social bot research featured on CACM, IEEE Computer covers
Congratulations to CASCI alumnus Dr. Ahmed Abdeen Hamed who was recognized by FastCompany magazine, among the most creative people in the world, in 2016, for his research publication entitled: Twitter K-H networks in action: Advancing biomedical literature for drug search.Dr. Hamed completed his Computer Science MS degree at Indiana University in May 2005 and joined our Complex Networks & Systems track of the PhD in Informatics in the Fall of 2008. For personal reasons, he finished his PhD at the University of Vermont, but started his research in biomedical text mining with the CASCI group.
Did more people see #thedress as blue and black or white and gold? How many Twitter users wanted pop star Katy Perry to take the #icebucketchallenge? The power to explore online social media movements — from the pop cultural to the political — with the same algorithmic sophistication as top experts in the field is now available to journalists, researchers and members of the public from a free, user-friendly online software suite released today by scientists at Indiana University. The Web-based tools, called the Observatory on Social Media, or “OSoMe” (pronounced “awesome”), provide anyone with an Internet connection the power to analyze online trends, memes and other online bursts of viral activity. An academic pre-print paper on the tools is available in the open-access journal PeerJ.
“This software and data mark a major goal in our work on Internet memes and trends over the past six years,” said Filippo Menczer, director of the Center for Complex Networks and Systems Research and a professor in the IU School of Informatics and Computing. “We are beginning to learn how information spreads in social networks, what causes a meme to go viral and what factors affect the long-term survival of misinformation online. The observatory provides an easy way to access these insights from a large, multi-year dataset.” Read more.