IDEAS home Printed from https://ideas.repec.org/r/inm/ormksc/v35y2016i3p343-362.html
   My bibliography  Save this item

Mining Brand Perceptions from Twitter Social Networks

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Saridakis, Charalampos & Katsikeas, Constantine S. & Angelidou, Sofia & Oikonomidou, Maria & Pratikakis, Polyvios, 2023. "Mining Twitter lists to extract brand-related associative information for celebrity endorsement," European Journal of Operational Research, Elsevier, vol. 311(1), pages 316-332.
  2. Junegak Joung & Ki-Hun Kim & Kwangsoo Kim, 2021. "Data-Driven Approach to Dual Service Failure Monitoring From Negative Online Reviews: Managerial Perspective," SAGE Open, , vol. 11(1), pages 21582440209, January.
  3. Purva Grover & Arpan Kumar Kar, 2017. "Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 203-229, September.
  4. Xuan Gong & Yunchan Zhu & Rizwan Ali & Ruijin Guo, 2019. "Capturing Associations and Sustainable Competitiveness of Brands from Social Tags," Sustainability, MDPI, vol. 11(6), pages 1-20, March.
  5. Maria Petrova & Ananya Sen & Pinar Yildirim, 2021. "Social Media and Political Contributions: The Impact of New Technology on Political Competition," Management Science, INFORMS, vol. 67(5), pages 2997-3021, May.
  6. Yang Gao & Wenjing Duan & Huaxia Rui, 2022. "Does Social Media Accelerate Product Recalls? Evidence from the Pharmaceutical Industry," Information Systems Research, INFORMS, vol. 33(3), pages 954-977, September.
  7. Silvia Blasi & Lorenzo & Silvia Rita Sedita, 2019. "Eco-friendliness and fashion perceptual attributes of fashion brands: an analysis of consumers’ perceptions based on Twitter data," "Marco Fanno" Working Papers 0237, Dipartimento di Scienze Economiche "Marco Fanno".
  8. Marchand, André & Hennig-Thurau, Thorsten & Flemming, Jan, 2021. "Social media resources and capabilities as strategic determinants of social media performance," International Journal of Research in Marketing, Elsevier, vol. 38(3), pages 549-571.
  9. Ning Zhong & David A. Schweidel, 2020. "Capturing Changes in Social Media Content: A Multiple Latent Changepoint Topic Model," Marketing Science, INFORMS, vol. 39(4), pages 827-846, July.
  10. Joaquin Sanchez & Carmen Abril & Michael Haenlein, 2020. "Competitive spillover elasticities of electronic word of mouth: an application to the soft drink industry," Journal of the Academy of Marketing Science, Springer, vol. 48(2), pages 270-287, March.
  11. Bag, Sujoy & Tiwari, Manoj Kumar & Chan, Felix T.S., 2019. "Predicting the consumer's purchase intention of durable goods: An attribute-level analysis," Journal of Business Research, Elsevier, vol. 94(C), pages 408-419.
  12. Jiwon Yang & Jay Hyuk Rhee, 2020. "CSR disclosure against boycotts: evidence from Korea," Asian Business & Management, Palgrave Macmillan, vol. 19(3), pages 311-343, July.
  13. Ishita Chakraborty & Minkyung Kim & K. Sudhir, 2019. "Attribute Sentiment Scoring With Online Text Reviews : Accounting for Language Structure and Attribute Self-Selection," Cowles Foundation Discussion Papers 2176, Cowles Foundation for Research in Economics, Yale University.
  14. Reckmann, Tobias, 2017. "Intellectual Structure and Emancipation of Word of Mouth Research: A Bibliometric Analysis of a Multidisciplinary Research Field," EconStor Preprints 179913, ZBW - Leibniz Information Centre for Economics.
  15. Carlson, Jamie & Rahman, Mohammad M. & Taylor, Alexander & Voola, Ranjit, 2019. "Feel the VIBE: Examining value-in-the-brand-page-experience and its impact on satisfaction and customer engagement behaviours in mobile social media," Journal of Retailing and Consumer Services, Elsevier, vol. 46(C), pages 149-162.
  16. Wen-Kuo Chen & Dalianus Riantama & Long-Sheng Chen, 2020. "Using a Text Mining Approach to Hear Voices of Customers from Social Media toward the Fast-Food Restaurant Industry," Sustainability, MDPI, vol. 13(1), pages 1-17, December.
  17. Mitra, Satanik & Jenamani, Mamata, 2020. "OBIM: A computational model to estimate brand image from online consumer review," Journal of Business Research, Elsevier, vol. 114(C), pages 213-226.
  18. Katsumata, Sotaro & Nishimoto, Akihiro & Kannan, P.K., 2023. "Brand competitiveness and resilience to exogenous shock: Usage of smartphone apps during the COVID-19 pandemic," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
  19. Gitto, Simone & Mancuso, Paolo, 2019. "Brand perceptions of airports using social networks," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 153-163.
  20. Pamuksuz, Utku & Yun, Joseph T. & Humphreys, Ashlee, 2021. "A Brand-New Look at You: Predicting Brand Personality in Social Media Networks with Machine Learning," Journal of Interactive Marketing, Elsevier, vol. 56(C), pages 55-69.
  21. Maximilian Matthe & Daniel M. Ringel & Bernd Skiera, 2023. "Mapping Market Structure Evolution," Marketing Science, INFORMS, vol. 42(3), pages 589-613, May.
  22. Bitty Balducci & Detelina Marinova, 2018. "Unstructured data in marketing," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 557-590, July.
  23. Christof Naumzik & Stefan Feuerriegel & Markus Weinmann, 2022. "I Will Survive: Predicting Business Failures from Customer Ratings," Marketing Science, INFORMS, vol. 41(1), pages 188-207, January.
  24. Qin, Chang-Xiong & Liu, Zhao, 2022. "Reference price effect of partially similar online products in the consideration stage," Journal of Business Research, Elsevier, vol. 152(C), pages 70-81.
  25. Hui Li & Jian Ni & Fangzhu Yang, 2024. "Product Design Using Generative Adversarial Network: Incorporating Consumer Preference and External Data," Papers 2405.15929, arXiv.org, revised Jun 2024.
  26. Dawn Iacobucci & Maria Petrescu & Anjala Krishen & Michael Bendixen, 2019. "The state of marketing analytics in research and practice," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 152-181, September.
  27. Ishita Chakraborty & Minkyung Kim & K. Sudhir, 2019. "Attribute Sentiment Scoring With Online Text Reviews : Accounting for Language Structure and Attribute Self-Selection," Cowles Foundation Discussion Papers 2176R2, Cowles Foundation for Research in Economics, Yale University, revised Jun 2021.
  28. Rietveld, Robert & van Dolen, Willemijn & Mazloom, Masoud & Worring, Marcel, 2020. "What You Feel, Is What You Like Influence of Message Appeals on Customer Engagement on Instagram," Journal of Interactive Marketing, Elsevier, vol. 49(C), pages 20-53.
  29. Anja Plumeyer & Pascal Kottemann & Daniel Böger & Reinhold Decker, 2019. "Measuring brand image: a systematic review, practical guidance, and future research directions," Review of Managerial Science, Springer, vol. 13(2), pages 227-265, April.
  30. Verena Schoenmueller & Oded Netzer & Florian Stahl, 2023. "Frontiers: Polarized America: From Political Polarization to Preference Polarization," Marketing Science, INFORMS, vol. 42(1), pages 48-60, January.
  31. Piyush Anand & Clarence Lee, 2023. "Using Deep Learning to Overcome Privacy and Scalability Issues in Customer Data Transfer," Marketing Science, INFORMS, vol. 42(1), pages 189-207, January.
  32. Djonata Schiessl & Helison Bertoli Alves Dias & José Carlos Korelo, 2022. "Artificial intelligence in marketing: a network analysis and future agenda," Journal of Marketing Analytics, Palgrave Macmillan, vol. 10(3), pages 207-218, September.
  33. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
  34. Kim, Hwang & Rao, Vithala R., 2022. "The role of network embeddedness across multiple social networks: Evidence from mobile social network games," International Journal of Research in Marketing, Elsevier, vol. 39(3), pages 867-887.
  35. Ashish Kumar Rathore & Santanu Das & P. Vigneswara Ilavarasan, 2018. "Social Media Data Inputs in Product Design: Case of a Smartphone," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 19(3), pages 255-272, September.
  36. Pradeep Chintagunta & Dominique M. Hanssens & John R. Hauser, 2016. "Editorial—Marketing Science and Big Data," Marketing Science, INFORMS, vol. 35(3), pages 341-342, May.
  37. Zheng Shen & Armida de la Garza, 2019. "Developing a Digital Artifact for the Sustainable Presentation of Marketing Research Results," Sustainability, MDPI, vol. 11(23), pages 1-22, November.
  38. Liu Liu & Daria Dzyabura & Natalie Mizik, 2020. "Visual Listening In: Extracting Brand Image Portrayed on Social Media," Marketing Science, INFORMS, vol. 39(4), pages 669-686, July.
  39. Petrova, Maria & Yildirim, Pinar & Sen, Ananya, 2017. "Social Media and Political Donations: New Technology and Incumbency Advantage in the United States," CEPR Discussion Papers 11808, C.E.P.R. Discussion Papers.
  40. Mithila Guha & Daniel Korschun, 2024. "Peer effects on brand activism: evidence from brand and user chatter on Twitter," Journal of Brand Management, Palgrave Macmillan, vol. 31(2), pages 153-167, March.
  41. Alzate, Miriam & Arce-Urriza, Marta & Cebollada, Javier, 2022. "Mining the text of online consumer reviews to analyze brand image and brand positioning," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
  42. Klostermann, Jan & Plumeyer, Anja & Böger, Daniel & Decker, Reinhold, 2018. "Extracting brand information from social networks: Integrating image, text, and social tagging data," International Journal of Research in Marketing, Elsevier, vol. 35(4), pages 538-556.
  43. Shrihari Sridhar & Eric Fang, 2019. "New vistas for marketing strategy: digital, data-rich, and developing market (D3) environments," Journal of the Academy of Marketing Science, Springer, vol. 47(6), pages 977-985, November.
  44. Safura M. Kallier Tar & Johannes A Wiid, 2021. "Consumer perceptions of real-time marketing used in campaigns for retail businesses," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(2), pages 86-105, March.
  45. Peiyao Li & Noah Castelo & Zsolt Katona & Miklos Sarvary, 2024. "Frontiers: Determining the Validity of Large Language Models for Automated Perceptual Analysis," Marketing Science, INFORMS, vol. 43(2), pages 254-266, March.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.