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In this workshop, Dr. Savvas Zannettou (TU Delft, Max Planck Institute for Informatics, International Data-driven Research for Advanced Modeling and Analysis Lab) will present two innovative methods: (1) Hawkes processes to model complex influence dynamics, (2) Analyzing multimodal data using contrastive learning. This workshop takes place in Roeterseiland Campus, and is hosted by Hosted by Newsflows ERC project & funded by the Social and Behavioural Data Science Centre. 
Event details of SoBe DSC workshop: Innovative methods to measure overtime information spread
Date
21 April 2023
Time
12:00 -18:00

About the workshop

During this workshop, Dr. Savvas Zannettou will present us with two innovative methodologies. 

During the first part of the workshop: Dr. Zannettou will cover innovative ways to measure how information spreads across time, events, and web communities and how these web entities influence one another. He will demonstrate how he has applied Hawkes processes to study how news, memes and hate speech spreads across web communities. By modeling the excitation between events, Hawkes processes, class of stochastic processes that are commonly used to model the arrival times of events in a given time period can help identify patterns of influence within a web community. This information can be used to detect influential users and communities, as well as to predict the likelihood of future events. Hawkes processes provide a powerful tool for modeling the complex dynamics across different entities and detecting patterns of influence among them across various social phenomena that involve the occurrence of events over time. By modeling the influence and interaction between individuals, groups, platforms, etc., researchers can gain new insights into the mechanisms driving social behavior and develop targeted interventions to promote positive social outcomes.

During the second part of the workshop: Dr. Zannettou will cover state-of-the-art approaches to analyzing multimodal data, in particular AI models that leverage the contrastive learning paradigm. These AI models allow us to assess the similarity of content across text and images, as well as extract semantic relationships on content irrespective of the content’s modality. Taken altogether, these methods can assist in making more comprehensive evaluations of how information spreads online and identify patterns of influence, irrespectively of the modality of the information (i.e., a piece of content that shares the same information in text and images). 

Time and location

Location: REC C10.20, Roeterseiland Campus

Time: 12:00 - 18:00

Note: If you are unable to attend the entire workshop, you are more than welcome to join only Part 1 or Part 2. Should you be too busy to attend either of these two parts, but you are eager to discuss these topics, you are also welcome to join the concluding drinks and networking session. You can indicate the extent of your participation via the link below.

Schedule:

Time Programme
12:00 - 12:15 Walk-ins & coffee
12:15 - 12:30 Round of introductions
12:30 - 13:30 Lunch & networking
13:30 - 14:30 Workshop part 1 – Hawkes processes 
14:30 - 15:00 Q&A + finding synergies across disciplines
15:00 - 15:15 Short coffee break
15:15 - 16:15 Workshop part 2 – Analyzing multimodal data
16:15 - 16:45 Q&A + finding synergies across disciplines
16:45 - 18:00

Drinks and networking

Questions about the workshop? Email Mónika Simon at m.simon@uva.nl.