Tag Archives: social

Postdoctoral Researcher in Analysis and Modeling of Social Networks

Network of Political Retweets

[UPDATE: this position has been filled.]

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 as early as possible after January 2013 for one year and is renewable for up to 2 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, other postdocs, 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 15 December 2012 will receive full consideration, but applications will be considered until the position is filled.

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.

Thanks to KDnuggets, SOCNET, Gephi, DBWorld, Air-L, CITASA and others for help in advertising this position.

PLEAD 2012 keynote

PLEAD 2012I 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 🙁

Truthy elections analytics tool

Science News cover

Truthy elections diffusion network

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.

Kinsey Reporter

Kinsey Reporter app screenshot
Kinsey Reporter app screenshot

Kinsey Reporter, currently in public beta release, is a global mobile platform for the reporting, visualization, and analysis of anonymous data about sexual and other intimate behaviors. It works on Android™ and iOS (iPhone®, iPad®, iPod touch®) devices and communicates securely with a central database server. The anonymous data collected with Kinsey Reporter is aggregated and shared openly with the community via an API at KinseyReporter.org.

With this citizen science project, we are exploring new ways to record and describe people’s sexual experiences worldwide. We hope to reach people with all kinds of different ideas, beliefs, and experiences, and who might be willing to report on sexual behaviors, regardless of who is involved and where it is observed. By using Kinsey Reporter, people contribute to research on human sexual behavior.

From a data science prospective, the project presents interesting challenges regarding how to collect, aggregate, visualize, and openly share crowdsourced data about sensitive topics, in a way that guarantees the anonymity of the data and the privacy of the volunteer citizen scientists. Our current protocol has been approved by the IU IRB for “non-human subjects research” thanks to the way we (1) aggregate geographic locations, (2) disallow uncontrolled input, and (3) completely disassociate the reported data from the identity of reporters, rather than attempting to anonymize personal identifiers.

NaN Team

Collaborators

Kinsey Reporter is a joint project with the  Kinsey Institute for Research in Sex, Gender, and Reproduction. The KI team includes:

Special thanks to Tracey TheriaultMartina DeplanoJennifer BassLynn LuckowGiancarlo RuffoEmilio FerraraKarissa McKelvey, and beta-testers (NaN, KI staff, friends & family). Finally, we gratefully acknowledge general support from the School of Informatics and Computing, the Office of the Vice Provost for Research, the Lilly EndowmentGoogle, and Special donors to The Kinsey Institute.

IARPA contract to study new ways to forecast critical societal events

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.

Competition among memes in a world with limited attention

Lilian

Meme diffusion networksIn 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.

DARPA award

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.

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.

Postdoctoral Researcher in Analysis and Modeling of Social Networks

Network of Political Retweets

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.

Thanks to KDnuggets, SOCNET, Gephi, DBWorld, Air-L, CITASA and others for help in advertising this position.

Science of Science

Scholarometer

Scholarometer is a social tool to facilitate citation analysis and help evaluate the impact of an author’s publications. One of the promises of Web Science is to leverage the wisdom of the crowds to give rise to emergent, bottom-up semantics, by making it easy for users to express relationships between arbitrary kinds of objects. Rather than starting with an ontology that determines the kinds of objects and relationships to be described and reasoned about, the idea is to give users the freedom to annotate arbitrary objects with arbitrary predicates, along with incentives for such annotations. Social tagging systems for images are one example, where the motivation can stem from the wish to organize and share one’s photos or from entertaining games to guess one another’s tags. The Scholarometer project explores a similar approach in the domain of scholarly publications. Scholarometer provides a service to scholars by computing citation-based impact measures. This motivates users to provide disciplinary annotations for authors, which in turn can be used to compute measures that allow to compare authors’ impact across disciplinary boundaries. This crowdsourcing approach can lead to emergent semantic networks to study interdisciplinary annotations and trends. To learn more please visit http://scholarometer.indiana.edu/about.html

Impact metrics

We proposed a method to quantify the disciplinary bias of any scholarly impact metric, and used this method to evaluate a number of established scholarly impact metrics. We introduced a simple universal metric that allows to compare the impact of scholars across scientific disciplines. This metric is now publicly available for scholars via Scholarometer.

We also developed a method to decouple the roles of quantity and quality of publications to explain how a certain level of impact is achieved. The method is based on the generation of a statistical baseline specifically tailored on the academic profile of each researcher. As an illustration, we used it to capture the quality of the work of Nobel laureates irrespective of number of publications, academic age, and discipline, even when traditional metrics indicate low impact in absolute terms. We further applied the methodology to almost a million scholars and over six thousand journals to measure the impact that cannot be explained by the volume of publications alone.

Emergence of fields

The birth and decline of disciplines are critical to science and society. How do scientific disciplines emerge? We developed an agent-based model in which the evolution of disciplines is guided mainly by social interactions among agents representing scientists. Disciplines emerge from splitting and merging of social communities in a collaboration network. We find that this social model can account for a number of stylized facts about the relationships between disciplines, scholars, and publications. These results provide strong quantitative support for the key role of social interactions in shaping the dynamics of science. While several “science of science” theories exist, this is the first account for the emergence of disciplines that is validated on the basis of empirical data.

We are currently exploring signals from coauthorship and citation networks to predict the emergence and decline of scientific fields.

Team members

Fil Menczer, PI
Fil Menczer
Sandro Flammini
Sandro Flammini
Stasa Milojevic
Stasa Milojevic
Santo Fortunato
Santo Fortunato
Aditya Tandon
Aditya Tandon
Diego R. Amancio
Diego R. Amancio
Filipi N. Silva
Filipi N. Silva
Wen Chen
Wen Chen
Filippo Radicchi
Filippo Radicchi
Jasleen Kaur
Jasleen Kaur
Mohsen JafariAsbagh
Mohsen JafariAsbagh
Snehal Patil
Snehal Patil
Xiaoling Sun
Xiaoling Sun
Lino Possamai
Lino Possamai
Diep Hoang
Diep Hoang

Project Publications:

Support

Our work on the emergence of fields is supported by US Navy grant N00174-17-1-0007.