Paper Type
Short
Paper Number
PACIS2025-1676
Description
Investors today navigate a constant flow of information from multiple digital sources, including traditional news media and user-generated content (UGC). These sources may convey divergent sentiment, creating challenges for making informed investment decisions. This study examines two key effects: (1) whether sentiment alignment (both positive or both negative) leads to more decisive investment actions compared to opposing sentiment (one positive, one negative), and (2) when news and UGC present conflicting sentiment, whether heuristic cues influence investment decisions. Using a randomized controlled experiment, we integrate cue consistency theory and the heuristic-systematic model (HSM) to explore how investors process sentiment-driven information in complex digital environments. This study aims to generate theoretical insights into decision-making under sentiment inconsistency and to offer practical implications for firms regarding strategic information disclosure and for investors seeking to mitigate sentiment-induced cognitive biases.
Recommended Citation
Nguyen, The Hong Hanh; Hu, Jin; Hu, Daning; and Chau, Michael, "Navigating Conflicting Sentiment: How News and User-Generated Content Shape Investment Decision-Making" (2025). PACIS 2025 Proceedings. 9.
https://aisel.aisnet.org/pacis2025/sm_digcollab/sm_digcollab/9
Navigating Conflicting Sentiment: How News and User-Generated Content Shape Investment Decision-Making
Investors today navigate a constant flow of information from multiple digital sources, including traditional news media and user-generated content (UGC). These sources may convey divergent sentiment, creating challenges for making informed investment decisions. This study examines two key effects: (1) whether sentiment alignment (both positive or both negative) leads to more decisive investment actions compared to opposing sentiment (one positive, one negative), and (2) when news and UGC present conflicting sentiment, whether heuristic cues influence investment decisions. Using a randomized controlled experiment, we integrate cue consistency theory and the heuristic-systematic model (HSM) to explore how investors process sentiment-driven information in complex digital environments. This study aims to generate theoretical insights into decision-making under sentiment inconsistency and to offer practical implications for firms regarding strategic information disclosure and for investors seeking to mitigate sentiment-induced cognitive biases.
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