Automated Marketing Research Using Online Customer Reviews

By Thomas Y. Lee, Eric T. Bradlow. 2011

449 citations recorded by the source corpus.

Subfields: Marketing, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/81b428b9965dde79388f18618641d0a0041bf15d

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Citations in the corpus

Examining the impact of luxury brand's social media marketing on customer engagement: Using big data analytics and natural language processing (2019, methodology): “Following this step, a large volume of textual elements of luxury brand tweets were coded to be compatible with other numeric variables so that the big data could be handled in a manageable way (Lee & Bradlow, 2011).”
A Semantic Approach for Estimating Consumer Content Preferences from Online Search Queries (2018, background): “There has been a stream of recent research in marketing that applies Natural Language Processing (NLP) to analyze online user-generated content (Archak et al., 2011; Lee and Bradlow, 2011; Netzer et al., 2012; Ghose et al., 2012).”
Consumer responses to functional, aesthetic and symbolic product design in online reviews (2017, background): “Online reviews contain rich, unsolicited consumer-generated content (Lee & Bradlow, 2011), offering a deep understanding of consumers' emotions (Kim &Gupta, 2012) and behaviors (Moon, Park, & Seog Kim, 2014).”
Mining Marketing Meaning from Online Chatter: Strategic Brand Analysis of Big Data Using Latent Dirichlet Allocation (2014, methodology): “Following prior studies (e.g., Lee and Bradlow 2011), we divided the sample into two time period samples: from 2005 to 2007 and 2007 to 2009.”
Marketing Analytics for Data-Rich Environments (2016, unknown): “Marketing models for large-scale unstructured data are still in their infancy, but research is starting to emerge (Lee and Bradlow 2011; Netzer et al. 2012).”
eWOM: Extant Research Review and Future Research Avenues (2016, background): “Lee and Bradlow (2011) present a very interesting possibility in their research.”
Topic Modeling in Management Research: Rendering New Theory from Textual Data (2019, background): “The groundbreaking and oft-cited work by Lee and Bradlow (2011) regarding automated online reviews has several features that have become norms for rendering with topic modeling, such as using triangulation (e.g., with k-means clustering and multidimensional scaling [MDS]), mapping structures,…”
Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content (2012, background): “The automated extraction of product attributes has also received attention in the recent marketing literature (Lee and Bradlow 2011).”
Digital marketing: A framework, review and research agenda (2017, unknown): “There is still much to be explored using such data (see for example, Lee & Bradlow, 2011) and our agenda for future research in Section 8 will outline some opportunities that exist in that space.”
Large-Scale Cross-Category Analysis of Consumer Review Content on Sales Conversion Leveraging Deep Learning (2019, background): “A handful of studies have applied NLP to marketing applications (Eliashberg et al., 2007;Decker and Trusov, 2010; Archak et al., 2011;Lee and Bradlow, 2011; Ghose et al., 2012b; Tirunillai and Tellis 2012; Liu et al. 2016; Lee et al. 2015).”
Machine learning and AI in marketing – Connecting computing power to human insights (2020, unknown): “Extracting features from unstructured data has been a popular usage of machine learning methods in marketing (Lee & Bradlow, 2011, Netzer et al., 2012, Tirunillai & Tellis, 2014, Liu & Toubia, 2018, Liu, Dzyabura, & Mizik, 2018, Liu, Lee, & Srinivasan, 2018, Zhang, Lee, et al., 2017, Dzyabura et…”
Mine Your Own Business: Market-Structure Surveillance Through Text Mining (2012, background): “Lee and Bradlow (2011) text mined semistructured product reviews to understand market structure based on the product attributes mentioned in the reviews.”