In the 21st century, brand communication has been significantly transformed through the interaction of users and artificial intelligence (AI), who co-create and recreate texts in digital environments. This evolution challenges traditional disciplines and roles, opening new perspectives for textual production on multiple platforms. The study examines the current state and application of the textual component in brand communication, exploring its disciplinary foundations, rhetorical traces, and research methodologies. To this end, a content analysis of 97 relevant publications from 2000 to 2024 was conducted, selected for their impact on the field of brand communication and following the guidelines established in the PRISMA statement. The results identified three sources of textual creation: Organization, users and algorithms. In addition, persuasion and sentiment take precedence at the rhetorical level, while data mining stands out in message analysis. In conclusion, the advertising text, which previously prevailed in brand communication with corporate authorship, formal prefiguration and a closed entity, now expands in a media and networked context. This text originates from a multiplicity of human and automated sources, overlapping rhetorical phases and fluid textualities. The shift implies a transition from unidirectional communication, characterized by repeated impacts, to multidirectional communication with spiraling trajectories and iterative adjustments. This challenges the boundaries of genres and formats, merging the persuasiveness of rhetoric and the imagination of storytelling. This situation demands commercial policies that integrate new professionals and roles, in partnership with the educational sector, and that address copyright with AI and users.

1. Ahn, J., La Ferle, C. (2008). Enhancing recall and recognition for brand names and body copy: A mixed-language approach. Journal of Advertising, 37(3), 107–117. https://doi.org/10.2753/JOA0091-3367370308
2. Al-Alshare, F. A. (2024). Measuring the dimensions of digital marketing in gaining customer satisfaction: A field study on customers of Jordanian pharmaceutical companies and distributors. Journal of Infrastructure, Policy and Development, 8(8): 5796. https://doi.org/10.24294/jipd.v8i8.5796
3. Araujo, T., Copulsky, J. R., Hayes, J. L., et al. (2020). From purchasing exposure to fostering engagement: Brand–consumer experiences in the emerging computational advertising landscape. Journal of Advertising, 49(4), 428–445. https://doi.org/10.1080/00913367.2020.1795756
4. Ashley, C., Oliver, J. D. (2010). Creative leaders. Journal of Advertising, 39(1), 115–130. https://doi.org/10.2753/JOA0091-3367390108
5. Atarama-Rojas, T., Vega-Foelsche, D. (2020). Corporate communications and branded content on Facebook: A study of the official accounts of Peruvian universities (Spanish). Revista de Comunicación, 19(1), 37–53. https://doi.org/10.26441/RC19.1-2020-A3
6. Baek, H., Ahn, J., Choi, Y., et al. (2012). Helpfulness of online consumer reviews: Readers’ objectives and review cues. International Journal of Electronic Commerce, 17(2), 123–140. https://doi.org/10.2753/JEC1086-4415170204
7. Bashari, B., Fazl-Ersi, E. (2020). Influential post identification on Instagram through caption and hashtag analysis. Measurement and Control, 53(3–4), 409–415. https://doi.org/10.1177/0020294019877489
8. Berger, J., Humphreys, A., Ludwig, S., et al. (2020). Uniting the tribes: Using text for marketing insight. Journal of Marketing, 84(1). https://doi.org/10.1177/0022242919873106
9. Bulmer, S., Palakshappa, N., Dodds, S., et al. (2024). Sustainability, brand authenticity and Instagram messaging. Journal of Business Research, 175, 114547. https://doi.org/10.1016/j.jbusres.2024.114547
10. Burmann, C., Arnhold, U. (2008). User generated branding: State of the art of research. LIT Verlag Münster.
11. Burns, K. S., Lutz, R. J. (2006). The function of format: Consumer responses to six on-line advertising formats. Journal of Advertising, 35(1), 53–64. https://doi.org/10.2753/JOA0091-3367350104
12. Calanchez, A., Chávez, K., de los Heros, C. H., et al. (2024). Green marketing in the promotion of environmentally responsible and sustainable practices in the development of resilient infrastructure in Peru: A systematic review. Journal of Infrastructure, Policy and Development. 8(9): 6337. https://doi.org/10.24294/jipd.v8i9.6337
13. Campbell, C., Pitt, L. F., Parent, M., et al. (2011). Understanding consumer conversations around ads in a Web 2.0 world. Journal of Advertising, 40(1), 87–102. https://doi.org/10.2753/JOA0091-3367400106
14. Cano Tenorio, R. (2019). Marketing techniques on the official Twitter accounts of flamenco artists (Spanish). ZER: Revista de Estudios de Comunicación, 24(46), 93–110. https://doi.org/10.1387/zer.20319
15. Carnevale, M., Luna, D., Lerman, D. (2017). Brand linguistics: A theory-driven framework for the study of language in branding. International Journal of Research in Marketing, 34(2), 572–591. https://doi.org/10.1016/j.ijresmar.2017.01.003
16. Casadei, P., Lee, N. (2020). Global cities, creative industries and their representation on social media: A micro-data analysis of Twitter data on the fashion industry. Environment and Planning A, 52(6), 1195–1220. https://doi.org/10.1177/0308518X20901585
17. Chakraborty, I., Kim, M., Sudhir, K. (2021). Attribute sentiment scoring with online text reviews: Accounting for language structure and missing attributes. Journal of Marketing Research, 59(3), 600–622. https://doi.org/10.1177/00222437211052500
18. Chan, E. Y., Meng, Y. (2023). They’re vs They Are: Contractions influence product choice and judgments. Journal of Business Research, 156, 113463. https://doi.org/10.1016/j.jbusres.2022.113463
19. Chang, C.-T. (2012). Missing ingredients in cause-related advertising. International Journal of Advertising, 31(2), 231–256. https://doi.org/10.2501/ija-31-2-231-256
20. Chatzipanagiotou, K., Azer, J., Ranaweera, C. (2023). E-WOM in the B2B context: Conceptual domain, forms, and implications for research. Journal of Business Research, 164, 113957. https://doi.org/10.1016/j.jbusres.2023.113957
21. Chen, G., Xie, P., Dong, J., Wang, T. (2019). Understanding programmatic creative: The role of AI. Journal of Advertising, 48(4). https://doi.org/10.1080/00913367.2019.1654421
22. Cheung, C. M. K., Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54(1), 461–470. https://doi.org/10.1016/j.dss.2012.06.008
23. Cheung, M. (2010). The globalization and localization of persuasive marketing communication: A cross-linguistic socio-cultural analysis. Journal of Pragmatics, 42(2), 413–430. https://doi.org/10.1016/j.pragma.2009.06.012
24. Chun, K. Y., Song, J. H., Hollenbeck, C. R., Lee, J.-H. (2014). Are contextual advertisements effective? International Journal of Advertising, 33(2), 351–371. https://doi.org/10.2501/IJA-33-2-351-371
25. Crolic, C., Thomaz, F., Hadi, R., Stephen, A. T. (2022). Blame the bot: Anthropomorphism and anger in customer–chatbot interactions. Journal of Marketing, 86(1), 132–148. https://doi.org/10.1177/00222429211045687
26. Cui, G., Lui, H. K., Guo, X. (2012). The effect of online consumer reviews on new product sales. International Journal of Electronic Commerce, 17(1), 39–62. https://doi.org/10.2753/JEC1086-4415170102
27. Dahlen, M., Rosengren, S. (2016). If advertising won’t die, what will it be? Toward a working definition of advertising. Journal of Advertising, 45(3), 334–345. https://doi.org/10.1080/00913367.2016.1172387
28. Daugherty, T., Eastin, M. S., Bright, L. (2008). Exploring consumer motivations for creating user-generated content. Journal of Interactive Advertising, 8(2), 16–25. https://doi.org/10.1080/15252019.2008.10722139
29. De Pelsmacker, P., Dens, N., Kolomiiets, A. (2018). The impact of text valence, star rating and rated usefulness in online reviews. International Journal of Advertising, 37(3), 340–359. https://doi.org/10.1080/02650487.2018.1424792
30. Deng, S., Tan, C. W., Wang, W., Pan, Y. (2019). Smart generation system of personalized advertising copy and its application to advertising practice and research. Journal of Advertising, 48(4), 356–365. https://doi.org/10.1080/00913367.2019.1652121
31. Du, R. Y., Netzer, O., Schweidel, D. A., Mitra, D. (2021). Capturing marketing information to fuel growth. Journal of Marketing, 85(1), 163–183. https://doi.org/10.1177/0022242920969198
32. Duff, B. R. L., Segijn, C. M. (2019). Advertising in a media multitasking era: Considerations and future directions. Journal of Advertising, 48(1). https://doi.org/10.1080/00913367.2019.1585306
33. Fan, Y.-W., Miao, Y.-F. (2012). Effect of electronic word-of-mouth on consumer purchase intention: The perspective of gender differences. International Journal of Electronic Business Management, 10(3), 175–181. https://doi.org/10.4236/ojbm.2017.53047
34. Findlay, K. (2018). The “shape” of interaction networks on Twitter. International Journal of Market Research, 60(5), 439–462. https://doi.org/10.1177/1470785318765695
35. Ford, J., Jain, V., Wadhwani, K., Gupta, D. G. (2023). AI advertising: An overview and guidelines. Journal of Business Research, 166, 114124. https://doi.org/10.1016/j.jbusres.2023.114124
36. Fu, J.-R., Chen, J. H. F. (2012). An investigation of factors that influence blog advertising effectiveness. International Journal of Electronic Business Management, 10(3), 194–203.
37. Gómez Vargas, M., Galeano Higuita, C., Jaramillo Muñoz, D. A. (2015). The state of the art: A research methodology (Spanish). Revista Colombiana de Ciencias Sociales, 6(2), 423–442.
38. Gunasekar, S., Kumar, D. S., Purani, K., et al. (2021). Understanding service quality attributes that drive user ratings: A text mining approach. Journal of Vacation Marketing, 27(4), 400–419. https://doi.org/10.1177/13567667211003246
39. Ha, Y., Park, K., Kim, S. J., et al. (2020). Automatically detecting image–text mismatch on Instagram with deep learning. Journal of Advertising, 50(1), 52–62. https://doi.org/10.1080/00913367.2020.1843091
40. Hackley, C., Hackley, A. R. (2019). Advertising at the threshold: Paratextual promotion in the era of media convergence. Marketing Theory, 19(2), 195–215. https://doi.org/10.1177/1470593118787581
41. Helberger, N., Huh, J., Milne, G., et al. (2020). Macro and exogenous factors in computational advertising: Key issues and new research directions. Journal of Advertising, 49(4), 377–393. https://doi.org/10.1080/00913367.2020.1811179
42. Hocutt, D. L. (2024). Composing with generative AI on digital advertising platforms. Computers and Composition, 71, 102829. https://doi.org/10.1016/j.compcom.2024.102829
43. Hong, S., Pittman, M. (2020). eWOM anatomy of online product reviews: Interaction effects of review number, valence, and star ratings on perceived credibility. International Journal of Advertising, 39(7), 892–920. https://doi.org/10.1080/02650487.2019.1703386
44. Huang, G. (2019). Variation matters: How to curb ad intrusiveness for native advertising on Facebook, Twitter, and Instagram. Internet Research, 29(6), 1469–1484. https://doi.org/10.1108/INTR-12-2017-0524
45. Huang, Y., Liu, H., Li, W., et al. (2020). Lifestyles in Amazon: Evidence from online reviews enhanced recommender system. International Journal of Market Research, 62(6). https://doi.org/10.1177/1470785319844146
46. Hung, K., Tse, D. K., Chan, T. H. (2021). E-commerce influencers in China: Dual-route model on likes, shares, and sales. Journal of Advertising, 50(4), 486–501. https://doi.org/10.1080/00913367.2021.1990811
47. Janssens, W., de Pelsmacker, P., Geuens, M. (2012). Online advertising and congruency effects. International Journal of Advertising, 31(3), 579–604. https://doi.org/10.2501/ija-31-3-579-604
48. Kahya-Özyirmidokuz, E. (2016). Analyzing unstructured Facebook social network data through web text mining: A study of online shopping firms in Turkey. Information Development, 32(1). https://doi.org/10.1177/0266666914528523
49. Killoran, J. B. (2010). Writing for robots: Search engine optimization of technical communication business web sites. Technical Communication, 57(2), 161–181.
50. Kim, D., Benbasat, I. (2009). Trust-assuring arguments in B2C e-commerce: Impact of content, source, and price on trust. Journal of Management Information Systems, 26(3), 175–206. https://doi.org/10.2753/MIS0742-1222260306
51. Kim, M., Song, D. (2017). When brand-related UGC induces effectiveness on social media: The role of content sponsorship and content type. International Journal of Advertising, 37(1), 105–124. https://doi.org/10.1080/02650487.2017.1349031
52. Kim, T., Hwang, S., Kim, M. (2022). Text analysis of online customer reviews for products in the FCB quadrants: Procedure, outcomes, and implications. Journal of Business Research, 150, 676–689. https://doi.org/10.1016/j.jbusres.2022.05.077
53. Knoll, J. (2016). Advertising in social media: A review of empirical evidence. International Journal of Advertising, 35(2), 266–300. https://doi.org/10.1080/02650487.2015.1021898
54. Koiso-Kanttila, N. (2004). Digital content marketing: A literature synthesis. Journal of Marketing Management, 20(1–2). https://doi.org/10.1362/026725704773041122
55. Kononova, A., Kim, W., Joo, E., Lynch, K. (2020). Click, click, ad: The proportion of relevant (vs. irrelevant) ads matters when advertising within paginated online content. International Journal of Advertising, 39(7), 1031–1058. https://doi.org/10.1080/02650487.2020.1732114
56. Kostygina, G., Feng, M., Czaplicki, L., et al. (2021). Exploring the discursive function of hashtags: A semantic network analysis of JUUL-related Instagram messages. Social Media and Society, 7(4). https://doi.org/10.1177/20563051211055442
57. Kumar, V., Gupta, S. (2016). Conceptualizing the evolution and future of advertising. Journal of Advertising, 45(3). https://doi.org/10.1080/00913367.2016.1199335
58. Kuo, Y.-F., Lin, C. S., Liu, L.-T. (2022). The effects of framing messages and cause-related marketing on backing intentions in reward-based crowdfunding. Journal of Retailing and Consumer Services, 64, 102799. https://doi.org/10.1016/j.jretconser.2021.102799
59. Kwak, H. (2012). Self-disclosure in online media: An active audience perspective. International Journal of Advertising, 31(3). https://doi.org/10.2501/IJA-31-3-485-510
60. Labrador, B., Ramón, N., Alaiz-Moretón, H., Sanjurjo-González, H. (2014). Rhetorical structure and persuasive language in the subgenre of online advertisements. English for Specific Purposes, 34(1). https://doi.org/10.1016/j.esp.2013.10.002
61. Lasmi, H., Lee, C. H., Ceran, Y. (2021). Popularity Brings Better Sales or Vice Versa: Evidence from Instagram and OpenTable. Global Business Review. https://doi.org/10.1177/09721509211044302
62. Lee, H., Cho, C. H. (2020). Digital advertising: Present and future prospects. International Journal of Advertising, 39(3). https://doi.org/10.1080/02650487.2019.1642015
63. Lee, J. K. (2021). Emotional expressions and brand status. Journal of Marketing Research, 58(6). https://doi.org/10.1177/00222437211037340
64. Li, H. (2019). Special section introduction: Artificial intelligence and advertising. Journal of Advertising, 48(4). https://doi.org/10.1080/00913367.2019.1654947
65. Li, H., Ma, L. (2020). Charting the path to purchase using topic models. Journal of Marketing Research, 57(6). https://doi.org/10.1177/0022243720954376
66. Li, M., Huang, L., Tan, C. H., Wei, K. K. (2013). Helpfulness of online product reviews as seen by consumers: Source and content features. International Journal of Electronic Commerce, 17(4). https://doi.org/10.2753/JEC1086-4415170404
67. Li, Y., Xie, Y. (2020). Is a picture worth a thousand words? An empirical study of image content and social media engagement. Journal of Marketing Research, 57(1), 1–19. https://doi.org/10.1177/0022243719881113
68. Libai, B., Bolton, R., Bügel, M. S., et al. (2010). Customer-to-customer interactions: Broadening the scope of word of mouth research. Journal of Service Research, 13(3). https://doi.org/10.1177/1094670510375600
69. Liu, X., Burns, A. C., Hou, Y. (2017). An investigation of brand-related user-generated content on Twitter. Journal of Advertising, 46(2), 236–247. https://doi.org/10.1080/00913367.2017.1297273
70. Liu-Thompkins, Y. (2019). A decade of online advertising research: What we learned and what we need to know. Journal of Advertising, 48(1). https://doi.org/10.1080/00913367.2018.1556138
71. Liu-Thompkins, Y., Maslowska, E., Ren, Y., Kim, H. (2020). Creating, metavoicing, and propagating: A road map for understanding user roles in computational advertising. Journal of Advertising, 49(4), 394–410. https://doi.org/10.1080/00913367.2020.1795758
72. Lou, C., Xie, Q. (2021). Something social, something entertaining? How digital content marketing augments consumer experience and brand loyalty. International Journal of Advertising, 40(3), 376–402. https://doi.org/10.1080/02650487.2020.1788311
73. Malenkina, N., Ivanov, S. (2018). A linguistic analysis of the official tourism websites of the seventeen Spanish autonomous communities. Journal of Destination Marketing & Management, 9, 204–233. https://doi.org/10.1016/j.jdmm.2018.01.007
74. Malthouse, E. C., Li, H. (2017). Opportunities for and pitfalls of using big data in advertising research. Journal of Advertising, 46(2), 227–235. https://doi.org/10.1080/00913367.2017.1299653
75. Mangiò, F., Mismetti, M., Lissana, E., Andreini, D. (2023). That’s the press, baby! How journalists co-create family business brands meanings: A mixed method analysis. Journal of Business Research, 161, 113842. https://doi.org/10.1016/j.jbusres.2023.113842
76. Maslowska, E., Segijn, C. M., Vakeel, K. A., Viswanathan, V. (2020). How consumers attend to online reviews: An eye-tracking and network analysis approach. International Journal of Advertising, 39(2), 282–306. https://doi.org/10.1080/02650487.2019.1617651
77. Mayrhofer, M., Matthes, J., Einwiller, S., Naderer, B. (2020). User-generated content presenting brands on social media increases young adults’ purchase intention. International Journal of Advertising, 39(1), 166–186. https://doi.org/10.1080/02650487.2019.1596447
78. Meeds, R. (2004). Cognitive and attitudinal effects of technical advertising copy: The roles of gender, self-assessed and objective consumer knowledge. International Journal of Advertising, 23(3). https://doi.org/10.1080/02650487.2004.11072887
79. Mukherjee, K., Banerjee, N. (2017). Effect of social networking advertisements on shaping consumers’ attitude. Global Business Review, 18(5), 1291–1306. https://doi.org/10.1177/0972150917710153
80. Muñiz, A. M., Schau, H. J. (2007). Vigilante marketing and consumer-created communications. Journal of Advertising, 36(3). https://doi.org/10.2753/JOA0091-3367360303
81. Muntinga, D. G., Moorman, M., Smit, E. G. (2011). Introducing COBRAs. International Journal of Advertising, 30(1), 13–46. https://doi.org/10.2501/IJA-30-1-013-046
82. Nam, H., Joshi, Y. V., Kannan, P. K. (2017). Harvesting brand information from social tags. Journal of Marketing, 81(4). https://doi.org/10.1509/jm.16.0044
83. Ni, D., Li, X., Xiao, Z., Gong, K. (2020). The power of words: A study of how search contents can affect financial decisions. Discrete Dynamics in Nature and Society. https://doi.org/10.1155/2020/1307092
84. O’Guinn, T., Allen, C., Semenik, R. (2013). Comprehensive brand advertising and promotion (Spanish). Available online: https://uachatec.com.mx/wp-content/uploads/2016/08/0.-Publicidad_y_Promocion_Integral_de_Marca_O_Guinn_Thomas_.pdf (accessed on 12 November 2024).
85. Oka, I. M. D., Subadra I. N. (2024). Digital marketing for sustainable tourism village in Bali: A mixed methods study. Journal of Infrastructure, Policy and Development, 8(7): 3726. https://doi.org/10.24294/jipd.v8i7.3726
86. Peng, J., Agarwal, A., Hosanagar, K., Iyengar, R. (2018). Network overlap and content sharing on social media platforms. Journal of Marketing Research, 55(4), 571–585. https://doi.org/10.1509/jmr.14.0643
87. PRISMA. (2020). PRISMA statement: Checklist. Available online: http://www.prisma-statement.org/PRISMAStatement/Checklist (accessed on 12 November 2024).
88. Puntoni, S., De Langhe, B., Van Osselaer, S. M. J. (2009). Bilingualism and the emotional intensity of advertising language. Journal of Consumer Research, 35(6), 1012–1025. https://doi.org/10.1086/595022
89. Qin, X., Jiang, Z. (2019). The impact of AI on the advertising process: The Chinese experience. Journal of Advertising, 48(4), 338–346. https://doi.org/10.1080/00913367.2019.1652122
90. Qirem, I. A. E., Alshehadeh, A. R., Elrefae, G. A., Eletter, S. (2024). Marketing investment and its impact on profitability and sustainable growth. Journal of Infrastructure, Policy and Development, 8(7), 4788. https://doi.org/10.24294/jipd.v8i7.4788
91. Schivinski, B., Dabrowski, D. (2016). The effect of social media communication on consumer perceptions of brands. Journal of Marketing Communications, 22(2), 189–214. https://doi.org/10.1080/13527266.2013.871323
92. Scolari, C. A. (2013). Transmedia narratives: When all media count (Spanish). Deusto.
93. Scolari, C. A. (2017). The transreader. Reading and transmedia narratives in the new ecology of communication (Spanish). Available online: https://hipermediaciones.com/2017/03/02/el-translector-lectura-y-narrativas-transmedia-en-la- nueva-ecologia-de-la-comunicacion/ (accessed on 12 November 2024).
94. Segev, S., Wang, W., Fernandes, J. (2014). The effects of ad-context congruency on responses to advertising in blogs: Exploring the role of issue involvement. International Journal of Advertising, 33(1), 17–36. https://doi.org/10.2501/IJA-33-1-017-036
95. Shulga, L. V., Busser, J. A., Bai, B., Kim, H. (2021). Branding co-creation with consumer-generated advertising: Effect on creators and observers. Journal of Advertising, 50(1), 5–23. https://doi.org/10.1080/00913367.2021.1978017
96. Steyn, P., Ewing, M. T., van Heerden, G., Pitt, L. F., Windisch, L. (2011). From whence it came. International Journal of Advertising, 30(1), 133–160. https://doi.org/10.2501/IJA-30-1-133-160
97. Tajvarpour, M. H., Pujari, D. (2022). The influence of narrative description on the success of crowdfunding campaigns: The moderating role of quality signals. Journal of Business Research, 149, 123–138. https://doi.org/10.1016/j.jbusres.2022.05.012
98. Teng, S., Khong, K. W., Goh, W. W. (2014). Conceptualizing persuasive messages using ELM in social media. Journal of Internet Commerce, 13(1), 65–87. https://doi.org/10.1080/15332861.2014.910729
99. Teng, S., Khong, W. K., Goh, W. W., Chong, A. Y. L. (2014). Examining the antecedents of persuasive eWOM messages in social media. Online Information Review, 38(6), 746–768. https://doi.org/10.1108/OIR-04-2014-0089
100. Van Noort, G., Himelboim, I., Martin, J., Collinger, T. (2020). Introducing a model of automated brand-generated content in an era of computational advertising. Journal of Advertising, 49(4), 411–427. https://doi.org/10.1080/00913367.2020.1795954
101. Voorveld, H. A. M. (2019). Brand communication in social media: A research agenda. Journal of Advertising, 48(1), 14–26. https://doi.org/10.1080/00913367.2019.1588808
102. Voorveld, H. A. M., van Noort, G., Muntinga, D. G., Bronner, F. (2018). Engagement with social media and social media advertising: The differentiating role of platform type. Journal of Advertising, 47(1), 38–54. https://doi.org/10.1080/00913367.2017.1405754
103. Wang, S., Kim, S. (Sam), Agrusa, J. (2018). A comparative study of perceptions of destination advertising according to message appeal and endorsement type. Asia Pacific Journal of Tourism Research, 23(1), 1–15. https://doi.org/10.1080/10941665.2017.1394336
104. Watts, J. (2018). Trend spotting: Using text analysis to model market dynamics. International Journal of Market Research, 60(4), 408–418. https://doi.org/10.1177/1470785318758558
105. Woodside, A. G. (2010). Brand-consumer storytelling theory and research: Introduction to a psychology & marketing special issue. Psychology and Marketing, 27(6), 531–540. https://doi.org/10.1002/mar.20342
106. Xu, X. (2019). Examining the relevance of online customer textual reviews on hotels’ product and service attributes. Journal of Hospitality and Tourism Research, 43(1), 141–163. https://doi.org/10.1177/1096348018764573
107. Xu, Y., Chen, W., Ow, T. T. (2023). The effects of social media posts’ characteristics on customer engagement: Evidence from WeChat. Information & Management, 60(7), 103854. https://doi.org/10.1016/j.im.2023.103854
108. Yoo, C. Y. (2011). Interplay of message framing, keyword insertion, and levels of product involvement in click-through of keyword search ads. International Journal of Advertising, 30(3), 399–424. https://doi.org/10.2501/IJA-30-3-399-424
109. Zhang, H., Choi, Y. K. (2017). Preannouncement messages: Impetus for electronic word-of-mouth. International Journal of Advertising, 37(1), 54–70. https://doi.org/10.1080/02650487.2017.1391679
110. Zhang, S., Gosselt, J. F., de Jong, M. D. T. (2020). How large information technology companies use Twitter: Arrangement of corporate accounts and characteristics of tweets. Journal of Business and Technical Communication, 34(4), 364–392. https://doi.org/10.1177/1050651920932191