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Title: Paths to Empathy: Heterogeneous Effects of Reading Personal Stories Online
Every day people share personal stories online, reaching millions of users around the world through blogs, social media and news websites. Why are some of these stories more attractive to readers than others? What features of these personal narratives make readers empathize with the storyteller? Do the readers’ personal characteristics and experiences play a role in feeling connection to the story they read? Experimental studies in psychology show that there are several factors that increase empathy in the aggregate, but there is a need for deeper understanding of empathetic feelings at the individual level of storyteller, story, and reader. Here, we present the design and analysis of a survey that studied the impact of story features and reader predispositions and perceptions on the empathy they feel when reading online stories. We use causal trees to find the individual-level causal factors for empathy and to understand the heterogeneity in the treatment effects. One of our main findings is that empathy is contextual and, while reader personality plays a significant role in evoking empathy, the mood of the reader prior to reading the story and linguistic story features have an impact as well. The results of our analyses can be used to help people create content that others care about and to help them communicate more effectively  more » « less
Award ID(s):
1801644
PAR ID:
10148687
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
Proceedings of IEEE Conference on Data Science and Advanced Analytics (DSAA)
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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