Research Note - When Do Consumers Value Positive vs. Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth

By Dezhi Yin, Sabyasachi Mitra, Han Zhang. Information systems research, 2015

350 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems and Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/c8505f0cd41dda5cf50752ca85761ce860e9145a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Han Zhang
2. Samuel D. Bond
3. Dezhi Yin

In Information Systems and Management

1. Han Zhang
2. Samuel D. Bond
3. Dezhi Yin

In Sociology and Political Science

1. Han Zhang
2. Dezhi Yin
3. Samuel D. Bond

Citations in the corpus

• Keep Your Cool or Let it Out: Nonlinear Effects of Expressed Arousal on Perceptions of Consumer Reviews (2017, background): “Prior research on antecedents of review helpfulness has highlighted factors such as numerical ratings, review timing, and product or reviewer characteristics (Chen and Lurie 2013; Forman, Ghose, and Wiesenfeld 2008; Mudambi and Schuff 2010; Yin, Mitra, and Zhang 2016).”