Generating Business Intelligence Through Social Media Analytics: Measuring Brand Personality with Consumer-, Employee-, and Firm-Generated Content

48 Pages Posted: 20 Jun 2018

See all articles by Yuheng Hu

Yuheng Hu

University of Illinois at Chicago, College of Business Administration

Yili Hong

Arizona State University (ASU) - W.P. Carey School of Business

David Gal

University of Illinois at Chicago

Anbang Xu

IBM Research

Vibha Sinha

IBM Research

Rama Akkiraju

IBM Research

Date Written: June 15, 2018

Abstract

Social media platforms have provided an enormous repository of textual data, which has brought about a grand opportunity in social media analytics, wherein valuable information can be extracted from content generated by users as well as firms. While research has shown the explicit value of social media in terms of its networking and campaign value, a growing literature is focused on extracting implicit valuable information embedded in the textual data. We showcase that firms can extract business value from social media data with an important business application in measuring brand personality. Specifically, we develop a text analytics framework that integrates different sources of social media data (consumer-generated content, employee-generated content, and firm-generated content) to measure brand personality. Based on Elastic-Net regression analysis of a large corpus of social media data, including self-descriptions of 1,996,214 consumers who followed the sample of brands, 312,400 employee reviews of the brands’ firms, and 680,056 brand official tweets, combining 10,950 consumer survey responses, we develop a brand personality model that achieves prediction accuracy as high as 0.78. Second, we find that the profile of individuals who choose to associate with brands on social media is an important predictor of brand personality; this provides the first real-world evidence for the raison d'être of research into the brand personality construct, namely a consumer identity-brand personality link. We also identify a link between an organization’s internal corporate environment and brand personality. We further illuminate the practical implication of our predictive model by building an information system that allows managers and analysts to explore and track personality of their own brands and their competitors’ brands.

Keywords: Social Media Analytics, Consumer-Generated Content, Employee-Generated Content, Firm-Generated Content, Brand Personality

Suggested Citation

Hu, Yuheng and Hong, Yili and Gal, David and Xu, Anbang and Sinha, Vibha and Akkiraju, Rama, Generating Business Intelligence Through Social Media Analytics: Measuring Brand Personality with Consumer-, Employee-, and Firm-Generated Content (June 15, 2018). Available at SSRN: https://ssrn.com/abstract=3197420 or http://dx.doi.org/10.2139/ssrn.3197420

Yuheng Hu

University of Illinois at Chicago, College of Business Administration ( email )

601 S Morgan St
Chicago, IL 60607
United States

HOME PAGE: http://yuhenghu.com

Yili Hong (Contact Author)

Arizona State University (ASU) - W.P. Carey School of Business ( email )

Tempe, AZ 85287-3706
United States

HOME PAGE: http://yilihong.github.io/

David Gal

University of Illinois at Chicago ( email )

1200 W Harrison St
Chicago, IL 60607
United States

Anbang Xu

IBM Research ( email )

T. J. Watson Research Center
1 New Orchard Road
Armonk, NY 10504-1722
United States

Vibha Sinha

IBM Research ( email )

T. J. Watson Research Center
1 New Orchard Road
Armonk, NY 10504-1722
United States

Rama Akkiraju

IBM Research ( email )

T. J. Watson Research Center
1 New Orchard Road
Armonk, NY 10504-1722
United States

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