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Do online word-of-mouth effects differ across platforms?

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Do online word-of-mouth effects differ

across platforms?

A comparison between Reddit and Twitter

Huub Kuiper S2707101 University of Groningen

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Topic introduction

› Customer Satisfaction § ACSI § Word-of-mouth (Anderson 1998) § Electronic word-of-mouth - Twitter - Reddit

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Prior research on eWOM effects

› Twitter

§ Positive relationship with respect to stock returns.

- Hourly level (Deng et al. 2018) - Daily level (Smailovic 2013)

§ Kind of sentiment

- Magnitude is higher for negative sentiment (Lui 2017)

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Hypotheses

› H1: eWOM found on Reddit performs better in predicting yearly stock returns than Twitter.

› H2: A model including both Reddit and Twitter eWOM as predictors

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Research Method

› Regressions between the predictors themselves.

› Regression between the predictors and the DV Stock Return.

§ Year Dummies § Lagged DV

› Weighted AIC (Wagenmakers & Farrell 2004)

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Data Collection

› Reddit Scraping

› Sentiment Analysis using qdap › Dataset size

§ 14,432 Reddit posts § 5+ million tweets

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Conclusions

› Negative Sentiment found on Reddit performs best in predicting other predictors.

› Change in negative Reddit sentiment performs second best in predicting stock returns.

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Discussion

› Lack of data in the used timespan

› Future research gives opportunity due to growth of platform › Improved scraping tools

› Time interval

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