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Dynamic Attitude Fixing: A novel theory of opinion dynamics in social networks and its implications for computational propaganda in hybrid social networks (containing humans and bots)

Project description

A new dynamic fixing theory of attitudes

Coordination attitudes are central in digitalised society, especially where hybrid social networks, incorporating humans and bots, intend to impact and shape economic and political processes. However, the network opinion dynamics model is not yet entirely understood. The EU-funded DAFINET project proposes a dynamic fixing theory of attitudes based on the presupposition that people simultaneously keep a reserve of multiple practices, express attitudes to create a social identity, and are subject to attitude expression in interaction. The project hypothesises that views can be dynamically fixed in social networks when sequences of attitudes are impulsive to identities through multilevel chains of agreement and disagreement. The theory will explain when and how consensus can spread rapidly across networks, the limits of identity-related attitude propagation, and how attitudes can return after events.


Understanding the coordination of attitudes in societies is vitally important for many disciplines and global social challenges. Network opinion dynamics are poorly understood, especially in hybrid networks where automated (bot) agents seek to influence economic or political processes (e.g. USA: Trump vs Clinton; UK: Brexit). A dynamic fixing theory of attitudes is proposed, premised on three features of attitudes demonstrated in ethnomethodology and social psychology; that people: 1) simultaneously hold a repertoire of multiple (sometimes ambivalent) attitudes, 2) express attitudes to enact social identity; and 3) are accountable for attitude expression in interaction. It is proposed that interactions between agents generate symbolic links between attitudes with the emergent social-symbolic structure generating perceived ingroup similarity and outgroup difference in a multilayer network. Thus attitudes can become dynamically fixed when constellations of attitudes are locked-in to identities via multilayer networks of attitude agreement and disagreement; a process intensified by conflict, threat or zero-sum partisan processes (e.g. elections/referenda). Agent-based simulations will validate the theory and explore the hypothesized channels of bot influence. Network experiments with human and hybrid networks will test theoretically derived hypotheses. Observational network studies will assess model fit using historical Twitter data. Results will provide a social-psychological-network theory for attitude dynamics and vulnerability to computational propaganda in hybrid networks.
The theory will explain:
(a) when and how consensus can propagate rapidly through networks (since identity processes fix attitudes already contained within repertoires);
(b) limits of identity-related attitude propagation (since attitudes outside of repertoires will not be easily adopted); and
(c) how attitudes can often ‘roll back’ after events (since contextual changes ‘unfix’ attitudes).

Host institution

Net EU contribution
€ 1 499 925,00
- Limerick

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Ireland Northern and Western Border
Activity type
Higher or Secondary Education Establishments
Total cost
€ 1 499 925,00

Beneficiaries (1)