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Trust Me: Film + Q&A (February 22, 2024, 5:30 Pm, Sheldon Museum Of Art) [Poster], Sheldon Museum Of Art, University Of Nebraska-Lincoln Feb 2024

Trust Me: Film + Q&A; (February 22, 2024, 5:30 Pm, Sheldon Museum Of Art) [Poster], Sheldon Museum Of Art, University Of Nebraska-Lincoln

Sheldon Museum of Art: Catalogs and Publications

Poster for Trust Me: Film + Q&A held February 22, 2024 at 5:30 PM at the Sheldon Museum of Art (University of Nebraska-Lincoln, Lincoln, Nebraska, United States).

Poster blurb:

In today's information landscape, how do you know whom--and what--you can trust? Watch the award-winning, feature-length documentary Trust Me, which explores how media technology is influencing society and what we can do about it.

A Q&A with Rosemary Smith, filmmaker and managing director of the non-partisan Getting Better Foundation, follows.

More information about the screening is available at https://news.unl.edu/newsrooms/today/article/trust-me-documentary-to-screen-at-sheldon/.

More information about the film is available at https://www.trustmedocumentary.com/ …


We’Ll Meet Again: Revealing Distributional And Temporal Patterns Of Social Contact, Thorsten Pachur, Lael J. Schooler, Jeffrey R. Stevens Jan 2014

We’Ll Meet Again: Revealing Distributional And Temporal Patterns Of Social Contact, Thorsten Pachur, Lael J. Schooler, Jeffrey R. Stevens

Department of Psychology: Faculty Publications

What are the dynamics and regularities underlying social contact, and how can contact with the people in one’s social network be predicted? In order to characterize distributional and temporal patterns underlying contact probability, we asked 40 participants to keep a diary of their social contacts for 100 consecutive days. Using a memory framework previously used to study environmental regularities, we predicted that the probability of future contact would follow in systematic ways from the frequency, recency, and spacing of previous contact. The distribution of contact probability across the members of a person’s social network was highly skewed, following an exponential …