Seeing the Forest for the Trees: New approaches to Characterizing and Forecasting Cascades

Cascades are a popular construct to observe and study information propagation (or diffusion) in social media such as Twitter and are defined using notions of influence, activity, or discourse commonality (e.g., hashtags). While these notions of cascades lead to different perspectives, primarily cascades are modeled as trees. We argue in this thesis an alternative viewpoint of cascades as forests (of trees) which yields a richer vocabulary of features to understand information propagation. We propose to develop a framework to extract forests and analyze their growth by studying their evolution at the tree-level and at the node-level. Furthermore, we outline four different problems that use the forest framework. First, we show that such forests of information cascades can be used to design counter-contagion algorithms to disrupt the spread of negative campaigns or rumors. Secondly, we demonstrate how such forests of information cascades can give us a rich set of features (structural and temporal), which can be used to forecast information flow. Thirdly, we argue that cascades modeled as forests can help us glean social network sensors to detect future contagious outbreaks that occur in the social network. To conclude, we show preliminary results of an approach - a generative model, that can describe information cascades modeled as forests and can generate synthetic cascades with empirical properties mirroring cascades extracted from Twitter.

Name thesis:degree_name

Ph. D.

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Computer Science and Applications

Department dc:contributor.department

Computer Science

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2018

Author dc:creator

• Krishnan, Siddharth

Chair dc:contributor.committeechair

• Heath, Lenwood S.

Committee members dc:contributor.committeemember

• Ras, Zbigniew W.
• Mitra, Tanushree
• Ribbens, Calvin J.
• Marathe, Madhav Vishnu

• Information cascades
• Forecasting

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

vt_gsexam:16470

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/83362