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June 3, 2026Open Access

Predicting Affect Dynamics during Naturalistic Viewing from Sentiment Analysis and Brain Functional Connectivity

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Authors

ZBZihan Bai

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Overview

Randomized trial explores predicting affect dynamics in individuals during natural viewing, highlighting potential insights into emotional measurement.

Key Points

  • The study aims to predict dynamic affective experiences during natural viewing using sentiment analysis and brain connectivity.
  • Utilized fine-grained sentiment analysis from movie descriptions to derive continuous sentiment representations.
  • Correlated sentiment data with behavioral valence and arousal ratings from 60 participants and fMRI data from 17 participants.
  • Clustered sentiment scores based on narrative elements such as topic, time, and location to improve context in analysis.
  • Automated sentiment analysis successfully predicted subjective valence on an event-level, showing effective correlation.
  • The sentence-level prediction of affective experience was found to be less reliable.
  • Developed clustering methods yielded a more accurate analysis of sentiment related to changes in the narrative context.

Cite This Study

Zihan Bai (2023) studied this question.

synapsesocial.com/papers/6a1fc64adee9eb8c0dce76d5https://doi.org/10.6082/a9wqy-zm953
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Neural signatures of shared subjective affective engagement and disengagement during movie viewing2024 · 8 citations
  2. 2Generalizable Neural Models of Emotional Engagement and Disengagement2024
  3. 3Inter‐ and intra‐subject similarity in network functional connectivity across a full narrative movie2024 · 6 citations
  4. 4Characterizing Relationships Between Fluctuating Cognitive and Neural States During Movie Watching2023
  5. 5A view-engage-predict framework for enhancing brain-behavior mapping with naturalistic movie-watching fMRI2026