nach oben

Erschienen in:

2022 | OriginalPaper | Buchkapitel

Automated Text Analysis

verfasst von : Ashlee Humphreys

Erschienen in: Handbook of Market Research

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

The amount of text available for analysis by marketing researchers has grown exponentially in the last two decades. Consumer reviews, message board forums, and social media feeds are just a few sources of data about consumer thought, interaction, and culture. However, written language is filled with complex meaning, ambiguity, and nuance. How can marketing researchers possibly transform this rich linguistic representation into quantifiable data for statistical analysis and modeling? This chapter provides an introduction to text analysis, covering approaches that range from top-down deductive methods to bottom-up inductive methods for text mining. After covering some foundational aspects of text analysis, applications to marketing research such as sentiment analysis, topic modeling, and studying organizational communication are summarized and explored, including a case study of word-of-mouth response to a product launch.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Partial Least Squares Structural Equation Modeling

Nächstes Kapitel Image Analytics in Marketing

Alba, J. W., & Hutchinson, J. W. (1987). Dimensions of consumer expertise. Journal of Consumer Research, 13(4), 411–454.

Arndt, J. (1967). Role of product-related conversations in the diffusion of a new product. Journal of Marketing Research, 4, 291–295.

Arsel, Z., & Bean, J. (2013). Taste regimes and market-mediated practice. Journal of Consumer Research, 39(5), 899–917.

Arvidsson, A., & Caliandro, A. (2016). Brand public. Journal of Consumer Research, 42(5), 727–748.

Barasch, A., & Berger, J. (2014). Broadcasting and narrowcasting: How audience size affects what people share. Journal of Marketing Research, 51(3), 286–299.

Belk, R. W., & Pollay, R. W. (1985). Images of ourselves: The good life in twentieth century advertising. Journal of Consumer Research, 11(4), 887.

Berelson, B. (1971). Content analysis in communication research. New York: Hafner.

Berger, J., & Milkman, K. L. (2012). What makes online content viral? Journal of Marketing Research, 49(2), 192–205.

Blei, David M., Andrew Y. Ng, & Michael I. Jordan. (2003). Latent dirichlet allocation. Journal of machine Learning research 3, 993–1022.

Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computer Science, 2(1), 1–8.

Boyd, R. L., & Pennebaker, J. W. (2015a). Away with words. In Consumer psychology in a social media world (p. 222). Abingdon: Routledge.

Boyd, R. L., & Pennebaker, J. W. (2015b). Did Shakespeare write double falsehood? Identifying individuals by creating psychological signatures with text analysis. Psychological Science, 26(5), 570–582.

Brown, J. J., & Reingen, P. H. (1987). Social ties and word-of-mouth referral behavior. Journal of Consumer Research, 14(3), 350–362.

Büschken, J., & Allenby, G. M. (2016). Sentence-based text analysis for customer reviews. Marketing Science, 35(6), 953–975.

Carley, K. (1997). Network text analysis: The network position of concepts. In C. W. Roberts (Ed.), Text analysis for the social sciences: Methods for drawing statistical inferences from texts and transcripts. Mahwah: Lawrence Erlbaum.

Chung, C. K., & Pennebaker, J. W. (2013). Counting little words in Big Data. In Social cognition and communication (p. 25). New York: Psychology Press.

Collins, A. M., & Loftus, E. F. (1975). A spreading-activation theory of semantic processing. Psychological Review, 82(6), 407.

Constant, N., Davis, C., Potts, C., & Schwarz, F. (2009). The pragmatics of expressive content: Evidence from large corpora. Sprache und Datenverarbeitung, 33(1–2), 5–21.

De Choudhury M., Sundaram H., John A., & Seligmann D. D. (2008). Can blog communication dynamics be correlated with stock market activity? In Proceedings of the nineteenth ACM conference on hypertext and hypermedia, ACM, pp. 55–60

Duhachek, Adam, and Katie Kelting. (2009). Coping repertoire: Integrating a new conceptualization of coping with transactional theory. Journal of Consumer Psychology 19(3), 473–485.

Dunphy, D. M., Bullard, C.G., & Crossing, E.E.M. (1974). Validation of the general inquirer Harvard Iv Dictionary. Paper presented at the 1974 Pisa conference on content analysis, Pisa, Italy.

Ertimur, B., & Coskuner-Balli, G. (2015). Navigating the institutional logics of markets: Implications for strategic brand management. Journal of Marketing, 79(2), 40–61.

Fishbein, M., & Ajzen, I. (1972). Attitudes and opinions. Annual Review of Psychology, 23(1), 487–544.

Fiss, P. C., & Hirsch, P. M. (2005). The discourse of globalization: Framing and sensemaking of an emerging concept. American Sociological Review, 70(1)., 24p.

Gamson, W. A., & Modigliani, A. (1989). Media discourse and public opinion on nuclear power: A constructionist approach. The American Journal of Sociology, 95(1), 1–37.

Gandolfo, A., Tuan, A., Corciolani, M., & Dalli, D. (2016). What do emerging economy firms actually disclose in their CSR reports? A longitudinal analysis. In CSR-HR Project (Corporate Social Responsability and Human Rights Project). Research Grant of University of Pisa (PRA_2015_0082).

Garrett, D. E. (1987). The effectiveness of marketing policy boycotts: Environmental opposition to marketing. Journal of Marketing, 51(2), 46–57.

Giesler, M. (2008). Conflict and compromise: drama in marketplace evolution. Journal of Consumer Research, 34(6), 739–753.

Godes, D., & Mayzlin, D. (2004). Using online conversations to study word-of-mouth communication. Marketing Science, 23(4), 545–560.

Godes, D., & Mayzlin, D. (2009). Firm-created word-of-mouth communication: Evidence from a field test. Marketing Science, 28(4), 721–739.

Grayson, K., & Rust, R. (2001). Interrater reliability assessment in content analysis. Journal of Consumer Psychology, 10(1/2), 71–73.

Grice, H. P. (1975). Logic and Conversation. Syntax and Semantics, vol.3 edited by P. Cole and J. Morgan, Academic Press. Reprinted as ch.2 of Grice 1989, 22–40.

Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political Analysis, 21(3), 267–297.

Homburg, C., Ehm, L., & Artz, M. (2015). Measuring and managing consumer sentiment in an online community environment. Journal of Marketing Research, 52(5), 629–641.

Hong, J., & Sternthal, B. (2010). The effects of consumer prior knowledge and processing strategies on judgments. Journal of Marketing Research, 47(2), 301–311.

Humphreys, A. (2010). Megamarketing: The creation of markets as a social process. Journal of Marketing, 74(2), 1–19.

Humphreys, A., & Latour, K. A. (2013). Framing the game: Assessing the impact of cultural representations on consumer perceptions of legitimacy. Journal of Consumer Research, 40(4), 773–795.

Humphreys, A., & Thompson, C. J. (2014). Branding disaster: Reestablishing trust through the ideological containment of systemic risk anxieties. Journal of Consumer Research, 41(4), 877–910.

Humphreys, A. (2015). Social media: Enduring principles. New York/Oxford: Oxford University Press.

Humphreys, A., & Wang, R. J.-H. (2018). Automated text analysis for consumer research. Journal of Consumer Research, 44(6), 1274–1306. https://doi.org/10.1093/jcr/ucx104CrossRef

Hutto, C. J., & Gilbert, E. (2014). Vader: A parsimonious rule-based model for sentiment analysis of social media text. In Eighth international AAAI conference on weblogs and social media.

Jia, L., Clement, Y., & Meng, W. (2009). The effect of negation on sentiment analysis and retrieval effectiveness. In Proceedings of the 18th ACM conference on information and knowledge management: ACM, pp. 1827–1830.

Jurafsky, D., Chahuneau, V., Routledge, B. R., & Smith, N. A. (2014). Narrative framing of consumer sentiment in online restaurant reviews. First Monday, 19(4). https://doi.org/10.5210/fm.v19i4.4944.

Kassarjian, H. H. (1977). Content analysis in consumer research. Journal of Consumer Research, 4(1), 8–19.

Kolbe, R. H., & Burnett, M. S. (1991). Content-analysis research: An examination of applications with directives for improving research reliability and objectivity. Journal of Consumer Research, 18(2), 243–250.

Kovács, B., Carroll, G. R., & Lehman, D. W. (2013). Authenticity and consumer value ratings: Empirical tests from the restaurant domain. Organization Science, 25(2), 458–478.

Kozinets, R. V. (2010). Networked narratives: Understanding word-of-mouth marketing in online communities. Journal of Marketing, 74(2), 71–89.

Kranz, P. (1970). Content analysis by word group. Journal of Marketing Research, 7(3), 377–380.

Krauss, J., Nann, S., Simon, D., Gloor, P. A., & Fischbach, K. (2008). Predicting movie success and academy awards through sentiment and social network analysis. In ECIS, pp. 2026–2037.

Lasswell, H. D., & Leites, N. (1949). Language of politics; studies in quantitative semantics. New York: G. W. Stewart.

Lee, F., Peterson, C., & Tiedens, L. Z. (2004). Mea culpa: Predicting stock prices from organizational attributions. Personality and Social Psychology Bulletin, 30(12), 1636–1649.

Lee, T. Y., & Bradlow, E. T. (2011). Automated marketing research using online customer reviews. Journal of Marketing Research, 48(5), 881–894.

Ludwig, S., Ko, d. R., Friedman, M., Brüggen, E. C., Wetzels, M., & Pfann, G. (2013). More than words: The influence of affective content and linguistic style matches in online reviews on conversion rates. Journal of Marketing, 77(1), 87–103.

Ludwig, S., Van Laer, T., De Ruyter, K., & Friedman, M. (2016). Untangling a web of lies: Exploring automated detection of deception in computer-mediated communication. Journal of Management Information Systems, 33(2), 511–541.

Maheswaran, D., & Sternthal, B. (1990). The effects of knowledge, motivation, and type of message on ad processing and product judgments. Journal of Consumer Research, 17(1), 66–73.

Maheswaran, D. (1994). Country of origin as a stereotype: Effects of consumer expertise and attribute strength on product evaluations. Journal of Consumer Research, 21(2), 354–365.

Maheswaran, D., Sternthal, B., & Gurhan, Z. (1996). Acquisition and impact of consumer expertise. Journal of Consumer Psychology, 5(2), 115.

Mahoney, J. (2003). Strategies of causal assessment in comparative historical analysis. In J. Mahoney & D. Rueschemeyer (Eds.), Comparative historical analysis in the social sciences. Cambridge, UK/New York: Cambridge University Press. pp. xix, 444.

Mankad, S., Han, H. S., Goh, J., & Gavirneni, S. (2016). Understanding online hotel reviews through automated text analysis. Service Science, 8(2), 124–138.

Mehl, M. R., & Gill, A. J. (2008). Automatic text analysis. In S. D. G. J. A. Johnson (Ed.), Advanced methods for behavioral research on the internet. Washington, DC: American Psychological Association.

Mestyán, M., Yasseri, T., & Kertész, J. (2013). Early prediction of movie box office success based on Wikipedia activity big data. PLoS One, 8(8), e71226.

Meyers-Levy, J., & Tybout, A. M. (1989). Schema congruity as a basis for product evaluation. Journal of Consumer Research, 16(1), 39–54.

Mill, J. S. (1843). A system of logic, ratiocinative and inductive: Being a connected view of the principles of evidence, and methods of scientific investigation. London: J.W. Parker.

Moe, Wendy W., and Michael Trusov. (2011). The value of social dynamics in online product ratings forums. Journal of Marketing Research 48(3), 444–456.

Moe, W. W., & Schweidel, D. A. (2014). Social media intelligence. Cambridge, UK/New York: Cambridge University Press.

Mogilner, C., Kamvar, S. D., & Aaker, J. (2010). The shifting meaning of happiness. Social Psychological and Personality Science, 2(4), 395–402.

Money, R. B., Gilly, M. C., & Graham, J. L. (1998). Explorations of national culture and word-of-mouth referral behavior in the purchase of industrial services in the United States and Japan. Journal of Marketing, 62, 76–87.

Monroe, B. L., Colaresi, M. P., & Quinn, K. M. (2009). Fightin' words: Lexical feature selection and evaluation for identifying the content of political conflict. Political Analysis, 16(4), 372–403.

Moore, S. G. (2015). Attitude predictability and helpfulness in online reviews: The role of explained actions and reactions. Journal of Consumer Research, 42(1), 30–44.

Netzer, O., Feldman, R., Goldenberg, J., & Fresko, M. (2012). Mine your own business: Market-structure surveillance through text mining. Marketing Science, 31(3), 521–543.

Opoku, R., Abratt, R., & Pitt, L. (2006). Communicating brand personality: Are the websites doing the talking for the top South African business schools? Journal of Brand Management, 14(1–2), 20–39.

Packard, G., Moore, S. G., & McFerran, B. (2014). How can “I” help “you”? The impact of personal pronoun use in customer-firm agent interactions. MSI report, pp. 14–110.

Packard, G. M., & Wooten, D. B. (2013). Compensatory knowledge signaling in consumer word-of-mouth. Journal of Consumer Psychology 23(4), 434–450.

Palmquist, M. E., Carley, K., & Dale, T. (2009). Analyzing maps of literary and non-literary texts. In K. Krippendorff & M. A. Bock (Eds.), The content analysis reader (pp. 4120–4415). Thousand Oaks: Sage.

Pennebaker, J. W., Francis, M. E., & Booth, R. J. (2001). Linguistic inquiry and word count: Liwc 2001 (Vol. 71). Mahway: Lawrence Erlbaum Associates.

Pennebaker, J. W., & King, L. A. (1999). Linguistic styles: Language use as an individual difference. Journal of Personality and Social Psychology, 77(6)., 17p.

Petty, R. E., & Cacioppo, J. T. (1979). Issue involvement can increase or decrease persuasion by enhancing message-relevant cognitive responses. Journal of Personality and Social Psychology, 37(10), 1915.

Phelps, J. E., Lewis, R., Mobilio, L., Perry, D., & Raman, N. (2004). Viral marketing or electronic word-of-mouth advertising: Examining consumer responses and motivations to pass along email. Journal of Advertising Research, 44(4), 333–348.

Plaisant, C., Rose, J., Bei, Y., Auvil, L., Kirschenbaum, M. G., Smith, M. N., Clement T., & Lord G. (2006). Exploring erotics in emily Dickinson’s correspondence with text mining and visual interfaces. In Proceedings of the 6th ACM/IEEE-CS joint conference on digital libraries, ACM, pp. 141–150.

Potts, C., & Schwarz, F. (2010). Affective ‘this’. Linguistic Issues in Language Technology, 3(5), 1–30.

Quantcast. (2010a) Cnet monthly traffic (estimated). (www.quantcast.com/cnet.com).

Quantcast. (2010b). Amazon monthly traffic (estimated). (www.quantcast.com/amazon.com).

Rayson, P. (2009). Wmatrix: A web-based corpus processing environment. Edited by C. Department, Lancaster University, UK.

Salton, Gerard, and Michael J. McGill. (1983). Introduction to modern information retrieval McGraw-Hill. New York.

Schweidel, D. A., & Moe, W. W. (2014). Listening in on social media: A joint model of sentiment and venue format choice. Journal of Marketing Research, 51(4), 387–402.

Sennett, R. (2006). The culture of the new capitalism. New Haven: Yale University Press.

Snefjella, B., & Kuperman, V. (2015). Concreteness and psychological distance in natural language use. Psychological Science, 26(9), 1449–1460.

Spiller, S. A., & Belogolova, L. (2016). On consumer beliefs about quality and taste. Journal of Consumer Research, 43(6), 970–991.

Stephen, A. T., & Toubia, O. (2010). Deriving value from social commerce networks. Journal of Marketing Research, 47(2), 215–228.

Stevenson, T. H., & Swayne, L. E. (1999). The portrayal of African-Americans in business-to-business direct mail: A benchmark study. Journal of Advertising, 28(3), 25–35.

Stone, P. J. (1966). The general inquirer; a computer approach to content analysis. Cambridge: MIT Press.

Sujan, M. (1985). Consumer knowledge: Effects on evaluation strategies mediating consumer judgments. Journal of Consumer Research, 12(1), 31–46.

Tirunillai, S., & Tellis, G. J. (2012). Does chatter really matter? Dynamics of user-generated content and stock performance. Marketing Science, 31(2), 198–215.

Tirunillai, S., & Tellis, G. J. (2014). Mining marketing meaning from online chatter: Strategic brand analysis of big data using latent Dirichlet allocation. Journal of Marketing Research, 51(4), 463–479.

Van de Rijt, A., Shor, E., Ward, C., & Skiena, S. (2013). Only 15 minutes? The social stratification of fame in printed media. American Sociological Review, 78(2), 266–289.

Van Laer, T., Escalas J. E., Ludwig S., & Van den Hende E. A. (2017). What happens in Vegas stays on TripAdvisor? Computerized text analysis of narrativity in online consumer reviews.

Ordenes, V., Francisco, S. L., Ko, D. R., Grewal, D., & Wetzels, M. (2017). Unveiling what is written in the stars: Analyzing explicit, implicit, and discourse patterns of sentiment in social media. Journal of Consumer Research, 43(6), 875–894.

Weber, K. (2005). A toolkit for analyzing corporate cultural toolkits. Poetics, 33(3/4), 26p.

Weber, M. (1924). Towards a sociology of the press. Paper presented at the first congress of sociologists, Frankfurt.

Winer, R. S. (2009). New communications approaches in marketing: Issues and research directions. Journal of Interactive Marketing, 23(2), 108–117. https://doi.org/10.1016/j.intmar.2009.02.004.CrossRef

Zipf, G. K. (1932). Selected studies of the principle of relative frequency in language. Cambridge, MA: Harvard University Press.

Titel: Automated Text Analysis
verfasst von: Ashlee Humphreys
Verlag: Springer International Publishing
Buch: Handbook of Market Research
Print ISBN: 978-3-319-57411-0

Electronic ISBN: 978-3-319-57413-4

Copyright-Jahr: 2022
DOI: https://doi.org/10.1007/978-3-319-57413-4_26