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Article
Independent storage of different features of real-world objects in long-term memory

Utochkin I. S., Brady T. F.

Journal of Experimental Psychology: General. 2020. Vol. 149. No. 3. P. 530-549.

Book chapter
Climate Adaptation of “Smart City” by Assessing Bioclimatic Comfort for UBEM

Ilina I. N., Dunichkin I. V.

In bk.: Sustainability in Energy and Buildings. Singapore: Springer, 2020. P. 519-529.

Article
Interaction between PFC neural networks ultra-slow fluctuations and brain oscillations

Rooy M., Novikov N., Гуткин Б. С.

Izvestiya Vysshikh uchebnykh zavedeniy. Prikladnaya nelineynaya dinamika. 2020. Vol. 28. No. 1. P. 90-97.

Online workshop "Using Search Volume Data to Predict Protest Mobilization: Application in the US Context"

Event ended
The School of Politics and Governance and the School of Psychology are holding a joint online seminar on Tuesday, February 15, at 5pm. Dr. Jais Adam-Troian, Lecturer at the Department of Psychology at Keele University, will be giving a talk on "Using Search Volume Data to Predict Protest Mobilization: Application in the US Context".The working language is English.

Presenter: Dr. Jais Adam-Troian, Lecturer at the Department of Psychology at Keele University

Abstract: Protest mobilization is a key driver of social and political change within societies. Yet, the study of the psychosocial drivers of protest mobilization remains limited by methodological constraints, favoring a quasi-exclusive use of archival and/or survey data. In this talk we will present a novel methodological approach relying on Search Volume Data (i.e. Google Trends indices) to study the dynamics of  protest mobilization with regards to its social psychological determinants. In social identity perspective, the main factor mobilizing  individuals into collective action remains the extent to which they feel identified with a protesting group (i.e., social identification).  Although the link between social identification and collective action is well-established, current evidence relies mostly on self-report data.  We will show how we combined real-life protest counts in the US (2017-2020) with online search data (Google Trends) for pronouns indicating a 'group' mindset (first-person plural pronouns; e.g. 'we', 'us'). We will also present a step-by-step method for robust causal estimation drawing upon time series, multiverse and mixed model analyses which allowed us to predict both protest and protester counts over time. Finally, we will briefly discuss in what ways this method matters for the ecological study and quantification of protest mobilization dynamics.

Zoom-link

Password: 244965

Date and time: February 15, 5 p.m. 

Hope to see you and your PhD students at the seminar!