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Monitoring Digital Disinformation: Innovative Methods and Empirical Results

Thu, September 10, 2:00 to 3:30pm MDT (2:00 to 3:30pm MDT), TBA

Session Submission Type: Full Paper Panel

Session Description

Since the revelation that the St Petersburg based Internet Research Agency actively intervened in the 2016 US Presidential election, considerable effort has been invested by government agencies, academics and NGOs in trying to understand how and why interference and influence measures have been enacted and by whom, and just how much of a challenge they pose to the integrity of the liberal democratic order.
Whilst acknowledging this rapid growth and development, there remain significant limitations with the current state-of-the-art:
- Reflecting wider trends, there is a dominance of Twitter and Facebook based studies, and we know less about the exploitation of other platforms in terms of authoring and amplifying deliberately misleading communications.
- Evidence shows that disinformation tactics are getting more sophisticated and malign actors better at obfuscating their real identities.
- There are ongoing and fractious debates about measuring the impact and influence of disinforming communications, and what appropriate concepts and metrics might be.
- There is little understanding of the Russian strategic approach of the digital space, as demonstrated by the fact that the meddling with the Presidential election caught the US administration totally off guard.

This panel will discuss innovative methodologies, conceptualization efforts and empirical studies results to better understand how to measure, map and understand disinformation. The panel will gather multidisciplinary research teams from France, the United Kingdom and the United States bringing evidence and insights from large-scale projects involving multi-national data collection and analysis on disinformation. Drawing from past experience abroad and in the United States, this panel will help prepare for digital disinformation in the 2020 presidential election.

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