Re-presenting a Story by Emotional Factors using Sentimental Analysis Method

TL;DR

This study investigates how emotional factors influence memory recall and storytelling, using a CNN-based sentiment analysis trained on movie reviews to objectively evaluate emotional expression in summaries.

Contribution

It introduces a novel approach to assess emotional impact on memory retrieval through a sentiment analysis model trained on large-scale review data.

Findings

Depressed individuals tend to recall stories more negatively and less expressively.

Emotionally high individuals use more negative words and recall stories more vividly.

The model effectively quantifies emotional intensity in natural language summaries.

Abstract

Remembering an event is affected by personal emotional status. We examined the psychological status and personal factors; depression (Center for Epidemiological Studies - Depression, Radloff, 1977), present affective (Positive Affective and Negative Affective Schedule, Watson et al., 1988), life orient (Life Orient Test, Scheier & Carver, 1985), self-awareness (Core Self Evaluation Scale, Judge et al., 2003), and social factor (Social Support, Sarason et al., 1983) of undergraduate students (N=64) and got summaries of a story, Chronicle of a Death Foretold (Gabriel Garcia Marquez, 1981) from them. We implement a sentimental analysis model based on convolutional neural network (LeCun & Bengio, 1995) to evaluate each summary. From the same vein used for transfer learning (Pan & Yang, 2010), we collected 38,265 movie review data to train the model and then use them to score summaries of each student. The results of CES-D and PANAS show the relationship between emotion and memory retrieval as follows: depressed people have shown a tendency of representing a story more negatively, and they seemed less expressive. People with full of emotion - high in PANAS - have retrieved their memory more expressively than others, using more negative words then others. The contributions of this study can be summarized as follows: First, lightening the relationship between emotion and its effect during times of storing or retrieving a memory. Second, suggesting objective methods to evaluate the intensity of emotion in natural language format, using a sentimental analysis model.