Consumer Behavior

Exploring Black Friday Using Sentiment Analysis and Topic Modeling

Authors
  • Ran Huang (Indiana University - Bloomington)
  • Sharron J. Lennon (Indiana Univeristy)
  • Minjeong Kim (Indiana University)
  • Ujwala Shenoy (Indiana University Bloomington)
  • Bhushan Bapuso Yadav (Indiana University Bloomington)

Abstract

This study conducted exploratory research on consumers’ views on BF consumption through mining BF-related tweets posted from November 2006 – November 2020, using sentiment analysis and topic modeling. Results showed that tweets related to BF shopping were shown to be more negative than positive over the years. Topics of positive sentiments contain sales and online shopping, while topics of negative sentiments include stockouts and violence/death. Four major themes identified include festive experience, BF shopping and deals, BF misbehavior, and stock out. Changes of the topics were also identified over time. Findings through sentiment analysis and topic modeling provide evidence of changes in consumer beliefs and perceptions of BF shopping. The findings of this study complement existing BF research primarily based on cross-sectional surveys of BF shoppers.

Keywords: Black Friday Shopping, Sentiment Analysis, Topic Modeling, Big data analysis, Black Friday shopping, sentiment analysis, topic modeling, big data analysis

How to Cite:

Huang, R., Lennon, S. J., Kim, M., Shenoy, U. & Yadav, B. B., (2024) “Exploring Black Friday Using Sentiment Analysis and Topic Modeling”, International Textile and Apparel Association Annual Conference Proceedings 80(1). doi: https://doi.org/10.31274/itaa.17375

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Published on
23 Jan 2024
Peer Reviewed