The project, dubbed “Truthy,” makes use of complex computer models to analyze the sharing of information on social media to determine how popular sentiment, user influence, attention, social network structure, and other factors affect the manner in which information is disseminated. Additionally, an important goal of the Truthy project is to better understand how social media can be abused.
In recent weeks, the Truthy project has come under criticism from some, who have misrepresented its goals. Contrary to these claims, the Truthy project is not designed and has not been used to create a database of political misinformation to be used by the federal government to monitor the activities of those who oppose its policies.
Truthy is not intended and is not capable to determine whether a statement constitutes “misinformation.” The target is the study of the structural patterns of information diffusion.
For example, an email sent simultaneously to a million addresses is likely spam, even if we have no automatic way to determine whether its content is true or false. The assumption behind the Truthy effort is that an understanding of the spreading patterns may facilitate the identification of abuse, independent from the nature or political color of the communication.
The Truthy platform is not informed by political partisanship. While it provides support to study the evolution of communication in all portions of the political spectrum, the machine learning algorithms used to identify suspicious patterns of information diffusion are entirely oblivious to the possibly political partisanship of the messages.
8/28/2014 Update: Despite the clarifications in this post, Fox News and others continued to perpetrate their attacks to our research project and to the PI personally. Their accusations are based on false claims, supported by bits of text and figures selectively extracted from our writings and presented completely out of context, in misleading ways. None of the researchers were contacted for comments before these outlandish conspiracy theories were aired and published. There is a good dose of irony in a research project that studies the diffusion of misinformation becoming the target of such a powerful disinformation machine.
9/3/2104 Update: David Uberti wrote an accurate account of recent events in Columbia Journalism Review.
First, a few words about what the Truthy research project is not:
- a political watchdog
- a government probe of social media
- an attempt to suppress free speech
- a way to define “misinformation”
- a partisan political effort
- a database tracking hate speech
Facts about Truthy:
- Truthy is a research project of the Center for Complex Networks and Systems Research at the IU School of Informatics and Computing. It aims to study how information spreads on social media, such as Twitter.
- The project has focused on domains such as news, politics, social movements, scientific results, and trending social media topics. Researchers develop theoretical computer models and validate them by analyzing public data, mainly from the Twitter streaming API.
- Social media posts available through public APIs are processed without human intervention or judgment to visualize and study the spread of memes. We aim to build a platform to make these analytic tools easily accessible to social scientists, reporters, and the general public.
- An important goal of the project is to help mitigate misuse and abuse of social media by helping us better understand how social media can be potentially abused. For example: when social bots are used to create the appearance of human-generated communication (hence the name “truthy”). We study whether it is possible to automatically differentiate between organic content and so-called “astroturf.”
- Examples of research to date include analyses of geographic and temporal patterns in movements like Occupy Wall Street, societal unrest in Turkey, the polarization of online political discourse, the use of social media data to predict election outcomes and stock market movements, and the geographic diffusion of trending topics.
- On the more theoretical side, we have studied how individuals’ limited attention span affects what information we propagate and what social connections we make, and how the structure of social networks can help predict which memes are likely to become viral.
- Hundreds of researchers across the U.S. and the world are studying similar issues based on the same data and with analogous goals — these topics were studied well before the advent of social media.
Congratulations to Onur Varol, Emilio Ferrara, Chris Ogan, Fil Menczer, and Sandro Flammini for winning the ACM Web Science 2014 Best Paper Award with their paper Evolution of online user behavior during a social upheaval (preprint). In the paper, the authors study the pivotal role played by Twitter during the political mobilization of the Gezi Park movement in Turkey. By analyzing over 2.3 million tweets produced during 25 days of protest in 2013, the authors show that similarity in trends of discussion mirrors geographic cues. The analysis also reveals that the conversation becomes more democratic as events unfold, with a redistribution of influence over time in the user population. Finally, the study highlights how real-world events, such as political speeches and police actions, affect social media conversations and trigger changes in individual behavior.
Congratulations also go to Luca Aiello and Rossano Schifanella, both former visitors and members of CNetS, who won the Best Presentation Award with their talk on Reading the Source Code of Social Ties (preprint).
We are excited to announce that the ACM Web Science 2014 Conference will be hosted by our center on the beautiful IUB campus June 23–26, 2014. Web Science studies the vast information network of people, communities, organizations, applications, and policies that shape and are shaped by the Web, the largest artifact constructed by humans in history. Computing, physical, and social sciences come together, complementing each other in understanding how the Web affects our interactions and behaviors. Previous editions of the conference were held in Athens, Raleigh, Koblenz, Evanston, and Paris. The conference is organized on behalf of the Web Science Trust by general co-chairs Fil Menczer, Jim Hendler, and Bill Dutton. Follow us on Twitter and see you in Bloomington!
The DESPIC team at the Center for Complex Systems and Networks Research (CNetS) presented a demo of a new tool named BotOrNot at a DoD meeting held in Arlington, Virginia on April 23-25, 2014. BotOrNot (truthy.indiana.edu/botornot) is a tool to automatically detect whether a given Twitter user is a social bot or a human. Trained on Twitter bots collected by our lab and the infolab at Texas A&M University, BotOrNot analyzes over a thousand features from the user’s friendship network, content, and temporal information in real time and estimates the degree to which the account may be a bot. In addition to the demo, the DESPIC team (including colleagues at the University of Michigan) presented several posters on Scalable Architecture for Social Media Observatory, Meme Clustering in Streaming Data, Persuasion Detection in Social Streams, High-Resolution Anomaly Detection in Social Streams, and Early Detection and Analysis of Rumors. See more coverage of BotOrNot on PCWorld, IDS, BBC, Politico, and MIT Technology Review.
Congratulations to Lilian Weng, who successfully defended her Informatics PhD dissertation titled Information diffusion on online social networks. The thesis provides insights into information diffusion on online social networks from three aspects: people who share information, features of transmissible content, and the mutual effects between network structure and diffusion process. The first part delves into the limited human attention. The second part of Dr. Weng’s dissertation investigates properties of transmissible content, particularly into the topic space. Finally, the thesis presents studies of how network structure, particularly community structure, influences the propagation of Internet memes and how the information flow in turn affects social link formation. Dr. Weng’s work can contribute to a better and more comprehensive understanding of information diffusion among online social-technical systems and yield applications to viral marketing, advertisement, and social media analytics. Congratulations from her colleagues and committee members: Alessandro Flammini, YY Ahn, Steve Myers, and Fil Menczer!
On August 11, 2013, the New York Times published an article by Ian Urbina with the headline: I Flirt and Tweet. Follow Me at #Socialbot. The article reports on how socialbots (software simulating people on social media) are being designed to sway elections, to influence the stock market, even to flirt with people and one another. Fil Menczer is quoted: “Bots are getting smarter and easier to create, and people are more susceptible to being fooled by them because we’re more inundated with information.” The article also mentions the Truthy project and some of our 2010 findings on political astroturf.
Inspired by this, the writers of The Good Wife consulted with us on an episode in which the main character finds that a social news site is using a socialbot to bring traffic to the site, defaming her client. The episode aired on November 24, 2013, on CBS (Season 5 Episode 9, “Whack-a-Mole”). Good show!
ACM, the professional association of computer scientists and computing professionals, announced today that I was named a Distinguished Scientist. Here is the list of other ACM members who got this award. This is a great honor and I am grateful. But my thanks go especially to my many amazing collaborators (colleagues, postdocs, visiting scholars, and especially students) without whom my contributions and impact would not exist — this award is also yours!
And while I am bragging, let me also mention that I was recently named a Senior Research Fellow of The Kinsey Institute for Research in Sex, Gender, and Reproduction. This is another great honor and I am excited about our team’s collaboration with the Kinsey Institute on the Kinsey Reporter project. The Kinsey Institute has an awesome tradition of trailblazing research and I hope that we can make a small contribution to it. Thanks to both the Kinsey Reporter team and our Kinsey collaborators!
A story in Nature discusses a recent paper (preprint) from CNetS members Jasleen Kaur, Filippo Radicchi and Fil Menczer on the universality of scholarly impact metrics. In the paper, we present a method to quantify the disciplinary bias of any scholarly impact metric. We use the method to evaluate a number of established scholarly impact metrics. We also introduce a simple universal metric that allows to compare the impact of scholars across scientific disciplines. Mohsen JafariAsbagh integrated this metric into Scholarometer, a crowdsourcing system developed by our group to collect and share scholarly impact data. The Nature story highlight how one can use normalized impact metrics to rank all scholars, as illustrated in the widget shown here.
Congratulations to Przemyslaw Grabowicz, Luca Aiello, and Fil Menczer for winning the WICI Data Challenge. A prize of $10,000 CAD accompanies this award from the Waterloo Institute for Complexity and Innovation at the University of Waterloo. The Challenge called for tools and methods that improve the exploration, analysis, and visualization of complex-systems data. The winning entry, titled Fast visualization of relevant portions of large dynamic networks, is an algorithm that selects subsets of nodes and edges that best represent an evolving graph and visualizes it either by creating a movie, or by streaming it to an interactive network visualization tool. The algorithm is deployed in the movie generation tool of the Truthy system, which allows users to create, in near-real time, YouTube videos that illustrate the spread and co-occurrence of memes on Twitter. Przemek and Luca worked on this project while visiting CNetS in 2011 and collaborating with the Truthy team. Bravo!
On June 27, 2013, in Turin, within the celebrations of the Lagrange Prize and ISI Foundation’s 30th anniversary, Fil Menczer and nine other scientists were named ISI Fellows. The recognition is a tribute to researchers whose scientific contribution is of primary importance for the Institute. The official investiture took place on June 28th, 2013, during the conference The Being of Science, which highlighted the ways in which the Fellows’ research fields intertwine with the ISI scientific activities.
UPDATE: With legal review completed, we re-launched Kinsey Reporter V.2!
CNetS, in collaboration with The Kinsey Institute, has released Kinsey Reporter, a global mobile survey platform for collecting and sharing anonymous data about sexual and other intimate behaviors. The pilot project allows citizen observers around the world to use free applications now available for Apple and Android mobile platforms to not only report on sexual behavior and experiences, but also to share, explore and visualize the accumulated data.
This new platform will allow us to explore issues that have been challenging to study until now, such as the prevalence of unreported sexual violence in different parts of the world, or the correlation between various sexual practices like condom use, for example, and the cultural, political, religious or health contexts in particular geographical areas.
The Kinsey Institute’s longstanding seminal studies of sexual behaviors created a perfect synergy with research going on at CNetS related to mining big data crowd-sourced from mobile social media. The sensitive domain — sexual relations — added an intriguing challenge in finding a way to share useful data with the community while protecting the privacy and anonymity of the reporting volunteers.
To foster the study of the structure and dynamics of Web traffic networks, we are making available to the research community a large Click Dataset of
13 53.5 billion HTTP requests collected at Indiana University. Between 2006 and 2010, our system generated data at a rate of about 60 million requests per day, or about 30 GB/day of raw data. We hope that this data will help develop a better understanding of user behavior online and create more realistic models of Web traffic. The potential applications of this data include improved designs for networks, sites, and server software; more accurate forecasting of traffic trends; classification of sites based on the patterns of activity they inspire; and improved ranking algorithms for search results.
Read our latest paper titled Social Dynamics of Science in Nature Scientific Reports. Authors Xiaoling Sun, Jasleen Kaur, Staša Milojević, Alessandro Flammini & Filippo Menczer ask, How do scientific disciplines emerge? No quantitative model to date allows us to validate competing theories on the different roles of endogenous processes, such as social collaborations, and exogenous events, such as scientific discoveries. Here we propose 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.
[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.
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.
Network Science is a new journal for a new discipline — one using the network paradigm, focusing on actors and relational linkages, to inform research, methodology, and applications from many fields across the natural, social, engineering and informational sciences. Given growing understanding of the interconnectedness and globalization of the world, network methods are an increasingly recognized way to research aspects of modern society along with the individuals, organizations, and other actors within it. I serve on the editorial team together with several IU colleagues. Network Science is published by Cambridge University Press. For further details, visit the official website or the informal site here at IU.
I also serve on the editorial board of EPJ Data Science, a new journal that aims to address the challenges of extracting meaningful data from systems with ever increasing complexity, analyzing them in ways that allow new insights, generating data that is needed but not yet available, and finding new empirical laws, or more fundamental theories, concerning how any natural or artificial (complex) systems work. This open access journal covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital tracks of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.
We welcome two postdoctoral associates who just joined our center. Ruby Wang got her PhD in Physics from Central China Normal University in 2009. Emilio Ferrara got his PhD in Mathematics (Computer Science) from the University of Messina in Italy in 2012. Both will work on projects related to the diffusion of information in social media and social networks.
Congratulations to Karissa McKelvey for being one of six undergraduate students at Indiana University Bloomington who have received the 2011-12 Provost’s Award for Undergraduate Research and Creative Activity. A senior in the School of Informatics and Computing from Santa Rosa, Calif., Karissa is working with Filippo Menczer on the Truthy project, which analyzes and makes accessible a massive stream of data disseminated through social media. She is focusing on the design and development of an interactive Web interface to visualize and navigate the diffusion of memes on networks such as Twitter. The goal of the project is to empower researchers, journalists and ordinary citizens to visualize how information spreads online and identify critical factors of the diffusion process. Karissa recently presented her work at the 2012 Conference on Computer Supported Cooperative Work. She plans to pursue a Ph.D. and to conduct research that applies computational tools to fields such as political science.
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.