The Effect of Calorie Posting Regulation on Consumer Opinion: A Flexible Latent Dirichlet Allocation Model with Informative Priors
Published Online:21 Aug 2017https://doi.org/10.1287/mksc.2017.1048
References
- (1999) Annual deaths attributable to obesity in the United States. J. Amer. Medical Assoc. 282(16):1530–1538.Crossref, Google Scholar
- (2009) Topic significance ranking of LDA generative models. Buntine W, Grobelnik M, Mladenić D, Shawe-Taylor J, eds. Proc. Joint Eur. Conf. Machine Learn. Knowledge Discovery Databases: Part I, Lecture Notes Comput. Sci., Vol. 5781 (Springer, Berlin Heidelberg), 67–82.Crossref, Google Scholar
- (2011) Deriving the pricing power of product features by mining consumer reviews. Management Sci. 57(8):1485–1509.Link, Google Scholar
- (2009) Natural Language Processing with Python (O’Reilly Media Inc., Sebastopol, CA).Google Scholar
- (1990) Database models and managerial intuition: 50% model+50% manager. Management Sci. 36(8):887–899.Link, Google Scholar
- (2006) Dynamic topic models. Cohen D, Moore A, eds. Proc. 23rd Internat. Conf. Machine Learn. (ACM, New York), 113–120.Crossref, Google Scholar
- (2003) Latent Dirichlet allocation. J. Machine Learn. Res. 3:993–1022.Google Scholar
- (2005) Race differentials in obesity: The impact of place. J. Health Soc. Behav. 46(3):229–243.Crossref, Google Scholar
- (2011) Calorie posting in chain restaurants. Amer. Econom. J.: Econom. Policy 3(1):91–128.Crossref, Google Scholar
- (2016) Sentence-based text analysis for customer reviews. Marketing Sci. 35(6):953–975.Link, Google Scholar
- (2009) A density-based method for adaptive LDA model selection. Neurocomputing 72(7–9):1775–1781.Crossref, Google Scholar
- (2009) Reading tea leaves: How humans interpret topic models. Bengio Y, Schuurmans D, Lafferty JD, Williams CKI, Culotta A, eds. Adv. Neural Inform. Processing Systems, Vol. 22, 1–9.Google Scholar
- (2010) Estimating aggregate consumer preferences from online product reviews. Internat. J. Res. Marketing 27(4):293–307.Crossref, Google Scholar
- (2012) LIA at TREC 2012 Web track: Unsupervised search concepts identification from general sources of information. Proc. 21th Text Retrieval Conf. (TREC 2012), Gaithersburg, MD.Google Scholar
- (1983) Multiple hypergeometric functions: Probabilistic interpretations and statistical uses. J. Amer. Statist. Assoc. 78(383):628–637.Crossref, Google Scholar
- (2013) Supplementing menu labeling with calorie recommendations to test for facilitation effects. Amer. J. Public Health 103(9):1604–1609.Crossref, Google Scholar
- (2007) From story line to box office: A new approach for green-lighting movie scripts. Management Sci. 53(6):881–893.Link, Google Scholar
- (2009) Annual medical spending attributable to obesity: Payer and service specific estimates. Health Affairs 28(5):822–831.Crossref, Google Scholar
- (2012) Designing ranking systems for hotels on travel search engines by mining user-generated and crowdsourced content. Marketing Sci. 31(3):493–520.Link, Google Scholar
- (2013) Sequential and temporal dynamics of online opinion. Marketing Sci. 31(3):448–473.Link, Google Scholar
- (1993) The voice of the customer. Marketing Sci. 12(1):1–27.Link, Google Scholar
- (2004) Finding scientific topics. Proc. Natl. Acad. Sci. USA 101(Suppl 1):5228–5235.Crossref, Google Scholar
- (2012) Incorporating lexical priors into topic models. Proc. 13th Conf. Eur. Chapter Assoc. Comput. Linguistics, 204–213.Google Scholar
- (2013) FDA head says menu labeling “thorny” issue. Associated Press (March 12). http://www.foxnews.com/health/2013/03/12/fda-head-says-menu-labeling-thorny-issue.html.Google Scholar
- (1951) On information and sufficiency. Ann. Math. Statist. 22(1):79–86.Crossref, Google Scholar
- (2009) Menu labeling as a potential strategy for combating the obesity epidemic: A health impact assessment. Amer. J. Public Health 99(9):1680–1686.Crossref, Google Scholar
- (2011) Automated marketing research using online customer reviews. J. Marketing Res. 48(5):881–894.Crossref, Google Scholar
- (1991) Divergence measures based on the Shannon entropy. IEEE Trans. Inform. Theory 37(1):145–151.Crossref, Google Scholar
- (2011) Multi-aspect sentiment analysis with topic models. Spiliopoulou M, Wang H, Cook D, Pei J, Wang W, Zaïane O, Wu X, eds. Data Mining Workshops (ICDMW), 2011 IEEE 11th Internat. Conf. (IEEE Computer Society, Washington, DC), 81–88.Crossref, Google Scholar
- (2011) Big data: The next frontier for innovation, competition, and productivity. Report, McKinsey Global Institute, Chicago.Google Scholar
- (2008) Topic models conditioned on arbitrary features with Dirichlet-multinomial regression. Proc. Twenty-Fourth Conf. Annual Conf. Uncertainty Artificial Intelligence (AUAI Press, Arlington, VA).Google Scholar
- (2011) Optimizing semantic coherence in topic models. Proc. Conf. Empirical Methods Natural Language Processing, 262–272.Google Scholar
- (2012) Mine your own business: Market-structure surveillance through text mining. Marketing Sci. 31(3):521–543.Link, Google Scholar
- (1999) The impact of health claims on consumer search and product evaluation outcomes: Results from FDA experimental data. J. Public Policy Marketing 18(1):89–105.Crossref, Google Scholar
- (2004) The author-topic model for authors and documents. Proc. 20th Conf. Uncertainty Artificial Intelligence (AUAI Press, Arlington, VA), 487–494.Google Scholar
- (2007) Probabilistic topic models. Handbook Latent Semantic Anal. 427(7):424–440.Google Scholar
- (2014) Mining marketing meaning from chatter: Strategic brand analysis of big data using latent Dirichlet allocation. J. Marketing Res. 51(4):463–479.Crossref, Google Scholar
- (2006) Motion pictures: Consumers, channels, and intuition. Marketing Sci. 25(6):674–677.Link, Google Scholar
- (1993) Judgmental versus statistical prediction: Information asymmetry and combination rules. Psych. Sci. 4(1):58–62.Crossref, Google Scholar

