|Talks|

Divided We Stand: Methods and Tools to Represent, Understand, and Analyze a Digital Society

Visiting speaker
Past Talk
Giancarlo Ruffo
Associate Professor, University of Turin
Oct 9, 2019
2:00 pm
Oct 9, 2019
2:00 pm
In-person
4 Thomas More St
London E1W 1YW, UK
The Roux Institute
Room
100 Fore Street
Portland, ME 04101
Network Science Institute
2nd floor
Network Science Institute
11th floor
177 Huntington Ave
Boston, MA 02115
Network Science Institute
2nd floor
Room
58 St Katharine's Way
London E1W 1LP, UK

Talk recording

The interplay between structural segregation and opinion polarization has motivated the work of scientists, writers, artists, and activists during the years. Segregation can be also a facilitator for the diffusion of misinformation, and debates that take place on social media have also a strong impact on the evolution of the network itself. Moreover, the consolidation of echo-chambers and the emergence of bots are rapidly changing the way we interact with others, and they are forcing our societies to rethink themselves, the way we vote, the freedom of speech, censorship policies, and so on. Nevertheless, these phenomena need more investigations because their dynamics and the always changing surrounding context are difficult to be framed within a unique framework. We need a multidisciplinary approach, and scientists need many several computational tools from traditionally different areas of computer science. Complex network analysis, computational linguistics, machine learning provide many methdologies and techniques, and it is not always trivial to use them adequately. This talk presents a very subjective review of what we have done in the last few years in collaboration with many other colleagues to model the spread of misinformation in segregated networks, to analyse how users’ stance in polarized political debates may be tighltly connected to the underlying structure of relationships, and how algorithms can be used to provide more efficient tools to test structural balance in signed networks that perfectly describe polarized communities.

References

[1] LM Aiello, A Barrat, C Cattuto, G Ruffo, R Schifanella, Link creation and profile alignment in the aNobii social network, 2010 IEEE 2nd Int.. Conf. on Social Computing, 249-256

[2] LM Aiello, A Barrat, C Cattuto, G Ruffo, R Schifanella, Link creation and information spreading over social and communication ties in interest based online social network, EPJ Data Science 1 (1), 12

[3] LM Aiello, M. Deplano, R Schifanella, G Ruffo, People are Strange when you’re a Stranger: Impact and Influence of Bots on Social Networks, in Proc. of the 6th Intern. AAAI Conf. on Weblogs and Social Media (ICWSM’12), Dublin, Ireland, 2012

[4] M Tambuscio, G Ruffo, A Flammini, and F Menczer. 2015. Fact-checking Effect on Viral Hoaxes: A Model of Misinformation Spread in Social Networks. In Proc. of the 24th Int. Conf. on World Wide Web (WWW '15 Companion)

[5] M Tambuscio, D F M Oliveira, G L Ciampaglia, G Ruffo, Network segregation in a model of misinformation and fact-checking, Journal of Computational Social Science (2018) 1: 261

[6] M Tambuscio, G. Ruffo, Fact-checking strategies to limit urban legends spreading in a segregated society, to appear in Applied Network Science Journal, Springer

[7] M Lai, M Tambuscio, V Patti, P Rosso, G. Ruffo, Stance Polarity in Political Debates: a Diachronic Perspective of Network Homophily and Conversations on Twitter, submitted

[8] A T E Capozzi, V Patti, G Ruffo, and C Bosco. 2018. A Data Viz Platform as a Support to Study, Analyze and Understand the Hate Speech Phenomenon. In Proceedings of the 2nd International Conference on Web Studies (WS.2 2018), ACM

About the speaker
Giancarlo Ruffo, Ph.D, is Associate Professor of Computer Science at the University of Turin, Italy from 2006, and Adjunct Professor at Schools of Informatics and Computing, Indiana University from 2011. He has been ISI fellow (awarded by ISI Foundation) from 2015 to 2018, member of the Board of Directors of SAA - Scuola di Amministrazione Aziendale (the MBA School at the University of Turin) from 2015 to 2016, and the coordinator of the master's degree program in "Networks and Computational Systems" (Reti e Sistemi Informatici) at the Computer Science department from 2012 to 2017. His current research interests fall in the multidisciplinary research area of Computational Social Science and Network Science, with focus on data visualization and data-driven approaches to model the diffusion of misinformation, opinion polarization in social media. He also investigated research problems on web and data mining, recommendation systems, social media, distributed applications, peer-to-peer systems, security, and micro-payment schemes. He is the principal investigator of ARCS group http://arcs.di.unito.it, and he has led several research projects funded by private and public institutions. He has published more than 60 peer-reviewed papers in international journals and conferences, and he presented his work in many different venues around the world. Aside his academic work, he has been involved in many other professional activities as free-lance consultant in the last 20 years. In 2013 he co-founded NetAtlas s.r.l., a tech company specialized in mobile application development, social media services and data fusion platforms design. The company is still active and in good health, and it successfully exited its start-up status in 2016.
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Oct 09, 2019