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Improving Text Analysis Using Sentence Conjunctions and Punctuation

53 Pages Posted: 31 Jan 2017  

Joachim Bueschken

Catholic University of Eichstätt-Ingolstadt

Greg M. Allenby

Ohio State University (OSU) - Department of Marketing and Logistics

Date Written: January 31, 2017

Abstract

User generated content in the form of customer reviews, blogs or tweets is an emerging and rich source of data for marketers. Topic models have been successfully applied to such data, demonstrating that empirical text analysis benefits greatly from a latent variable approach which summarizes high-level interactions among words. We propose a new topic model that allows for serial dependency of topics in text. That is, topics may carry over from word to word in a document, violating the bag-of-words assumption in traditional topic models. In our model, topic carry-over is informed by sentence conjunctions and punctuation. Typically, such observed information is eliminated prior to analyzing text data (i.e., “pre-processing”) because words such as “and” and “but” do not differentiate topics. We find that these elements of grammar contain information relevant to topic changes. We examine the performance of our model using multiple data sets and estab- lish boundary conditions for when our model leads to improved inference about customer evaluations. Implications and opportunities for future research are discussed.

Keywords: LDA, autocorrelated topics, user-generated content, Bayesian analysis

JEL Classification: M31, C11

Suggested Citation

Bueschken, Joachim and Allenby, Greg M., Improving Text Analysis Using Sentence Conjunctions and Punctuation (January 31, 2017). Available at SSRN: https://ssrn.com/abstract=2908915

Joachim Bueschken (Contact Author)

Catholic University of Eichstätt-Ingolstadt ( email )

Auf der Schanz 49
Ingolstadt, D-85049
Germany
+498419371976 (Phone)
+498419372976 (Fax)

HOME PAGE: http://www.wfi.edu/mkt

Greg Allenby

Ohio State University (OSU) - Department of Marketing and Logistics ( email )

Fisher Hall 524
2100 Neil Ave
Columbus, OH 43210
United States

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