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        <title>e-Commerce and Sentiment Analysis: Predicting Outcomes of Class Action Lawsuits</title>
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    <abstract>In recent years, the focus of e-Commerce research has been on better understanding the relationship between the internet marketplace, customers, and goods and services. This has been done by examining information that can be gleaned from consumer information, recommender systems, click rates, or the way purchasers go about making buying decisions, for example. This paper takes a very different approach and examines the companies themselves. In the past ten years, e-Commerce giants such as Amazon, Skymall, Wayfair, and Groupon have been embroiled in class action security lawsuits promulgated under Rule 10b(5), which, in short, is one of the Securities and Exchange Commission’s main rules surrounding fraud. Lawsuits are extremely expensive to the company and can damage a company’s brand extensively, with the shareholders left to suffer the consequences. We examined the Management Discussion and Analysis and the Market Risks for 96 companies using sentiment analysis on selected financial measures and found that we were able to predict the outcome of the lawsuits in our dataset using sentiment (tone) alone to a recall of 0.8207 using the Random Forest classifier. We believe that this is an important contribution as it has cross-domain implications and potential, and opens up new areas of research in e-Commerce, finance, and law, as the settlements from the class action lawsuits in our dataset alone are in excess of $1.6 billion dollars, in aggregate.</abstract>
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%0 Conference Proceedings
%T e-Commerce and Sentiment Analysis: Predicting Outcomes of Class Action Lawsuits
%A Taylor, Stacey
%A Keselj, Vlado
%Y Malmasi, Shervin
%Y Kallumadi, Surya
%Y Ueffing, Nicola
%Y Rokhlenko, Oleg
%Y Agichtein, Eugene
%Y Guy, Ido
%S Proceedings of the 3rd Workshop on e-Commerce and NLP
%D 2020
%8 July
%I Association for Computational Linguistics
%C Seattle, WA, USA
%F taylor-keselj-2020-e
%X In recent years, the focus of e-Commerce research has been on better understanding the relationship between the internet marketplace, customers, and goods and services. This has been done by examining information that can be gleaned from consumer information, recommender systems, click rates, or the way purchasers go about making buying decisions, for example. This paper takes a very different approach and examines the companies themselves. In the past ten years, e-Commerce giants such as Amazon, Skymall, Wayfair, and Groupon have been embroiled in class action security lawsuits promulgated under Rule 10b(5), which, in short, is one of the Securities and Exchange Commission’s main rules surrounding fraud. Lawsuits are extremely expensive to the company and can damage a company’s brand extensively, with the shareholders left to suffer the consequences. We examined the Management Discussion and Analysis and the Market Risks for 96 companies using sentiment analysis on selected financial measures and found that we were able to predict the outcome of the lawsuits in our dataset using sentiment (tone) alone to a recall of 0.8207 using the Random Forest classifier. We believe that this is an important contribution as it has cross-domain implications and potential, and opens up new areas of research in e-Commerce, finance, and law, as the settlements from the class action lawsuits in our dataset alone are in excess of $1.6 billion dollars, in aggregate.
%R 10.18653/v1/2020.ecnlp-1.12
%U https://aclanthology.org/2020.ecnlp-1.12
%U https://doi.org/10.18653/v1/2020.ecnlp-1.12
%P 77-85

Markdown (Informal)

[e-Commerce and Sentiment Analysis: Predicting Outcomes of Class Action Lawsuits](https://aclanthology.org/2020.ecnlp-1.12) (Taylor & Keselj, ECNLP 2020)

• e-Commerce and Sentiment Analysis: Predicting Outcomes of Class Action Lawsuits (Taylor & Keselj, ECNLP 2020)

ACL

• Stacey Taylor and Vlado Keselj. 2020. e-Commerce and Sentiment Analysis: Predicting Outcomes of Class Action Lawsuits. In Proceedings of the 3rd Workshop on e-Commerce and NLP, pages 77–85, Seattle, WA, USA. Association for Computational Linguistics.