Automated Text Analysis for Consumer Research

By Ashlee Humphreys, Rebecca Jen-Hui Wang. 2018

530 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Marketing, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/af3e09b9a57b66c49ea0c900081c0f63042f87a9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Roland T. Rust
2. Ming-Hui Huang
3. Andre F. Maciel
4. Jamie Carlson
5. Eileen Fischer
6. Jennifer E. Rowley
7. Yogesh Kumar Dwivedi
8. Xia Liu

In Marketing

1. Ming-Hui Huang
2. Roland T. Rust
3. Yogesh Kumar Dwivedi
4. Jennifer E. Rowley
5. Jonah A. Berger
6. Elvira R. Ismagilova
7. Heikki Karjaluoto
8. Grant Packard

In Sociology and Political Science

1. Elvira R. Ismagilova
2. Roland T. Rust
3. Yogesh Kumar Dwivedi
4. Grant Packard
5. Ming-Hui Huang
6. Jonah A. Berger
7. Hyunju Shin
8. Xia Liu

Citations in the corpus

• Setting the future of digital and social media marketing research: Perspectives and research propositions (2020, background): “Here, advancements in social media monitoring, text and image analysis techniques that “listen” to, and capture, customer-generated content enable ideation, sharing, product development and brand experience improvements (Humphreys and Wang 2017; Villarroel Ordenes et al., 2018).”
• Examining the impact of luxury brand's social media marketing on customer engagement​: Using big data analytics and natural language processing (2019, methodology): “Automated text analytical approaches specified by Humphreys and Wang (2017) and Berger and Milkman (2012) were utilized to code a large number of firm tweets within a reasonable time frame.”
• Collaborative Market Driving: How Peer Firms Can Develop Markets Through Collective Action (2020, methodology): “As such, we collected these archives in a less structured way than in studies entailing automated text analysis, an approach that draws on predefined (vs. emergent) data sources and sampling parameters (Humphreys and Wang 2017).”
• How Language Shapes Word of Mouth's Impact (2017, background): “Others’ opinions shape everything from the everyday products people buy (Chevalier and Mayzlin 2006; Ho-Dac, Carson, and Moore 2014) to important medical and financial matters (Iyengar, Van den Bulte, and Valente 2011; Lin and Fang 2006).”
• A strategic framework for artificial intelligence in marketing (2020, background): “…and implicit language and discourse patterns, can be analyzed to understand consumer responses using their own language (Hewett et al. 2016; Humphreys and Wang 2018; Ordenes et al. 2017), the interaction between conversational AI and customers can be enhanced by applying analytical mapping…”