IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v30y2019i3p839-855.html
   My bibliography  Save this article

Understanding User-Generated Content and Customer Engagement on Facebook Business Pages

Author

Listed:
  • Mochen Yang

    (Kelley School of Business, Indiana University, Bloomington, Indiana 47405)

  • Yuqing Ren

    (Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455)

  • Gediminas Adomavicius

    (Carlson School of Management, University of Minnesota, Minneapolis, Minnesota 55455)

Abstract

With the growth and prevalence of social media platforms, many companies have been using them to engage with customers and encourage user-generated content (UGC) about their products and services. However, there has not been much research on the characteristics of UGC on these platforms and, correspondingly, their impact on customer engagement. In this paper, we analyze user-generated posts from Facebook business pages of multiple companies to understand what users post on Facebook business pages and how post valence and content characteristics affect engagement, measured as the number of likes and comments received by a post. We control for a variety of factors, including post linguistic features, poster characteristics, and post context heterogeneity. Our analysis demonstrates that for user-generated posts on Facebook business pages, negative posts are significantly more prevalent than positive posts, which contrasts with the J-shaped valence distribution of online consumer reviews. We also show that engagement depends not only on the valence of a post but also on the specific ways in which a post is positive or negative. We observe three types of customer complaints, respectively, related to product and service quality, money issues, and social and environmental issues. Our analyses show that social complaints receive more likes, but fewer comments, than quality or money complaints. Such nuances can only be uncovered by analyzing the actual post content, going beyond the valence of the posts. Furthermore, we theoretically discuss and empirically demonstrate that liking and commenting are engagement behaviors with different antecedents. For example, positive posts tend to attract more likes yet fewer comments than neutral posts. Overall, our research shows that user-generated posts on Facebook business pages represent a distinctive form of UGC that is conceptually different from online consumer reviews. Our work advances the knowledge on UGC and has practical implications for firms’ social media marketing strategy.

Suggested Citation

  • Mochen Yang & Yuqing Ren & Gediminas Adomavicius, 2019. "Understanding User-Generated Content and Customer Engagement on Facebook Business Pages," Information Systems Research, INFORMS, vol. 30(3), pages 839-855, September.
    • Handle: RePEc:inm:orisre:v:30:y:2019:i:3:p:839-855
    DOI: 10.1287/isre.2019.0834
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/isre.2019.0834
    Download Restriction: no
    File URL: https://libkey.io/10.1287/isre.2019.0834?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Unknown, 1967. "Index," 1967 Conference, August 21-30, 1967, Sydney, New South Wales, Australia 209796, International Association of Agricultural Economists.
    2. Sinan Aral & Chrysanthos Dellarocas & David Godes, 2013. "Introduction to the Special Issue ---Social Media and Business Transformation: A Framework for Research," Information Systems Research, INFORMS, vol. 24(1), pages 3-13, March.
    3. David Godes & Dina Mayzlin, 2009. "Firm-Created Word-of-Mouth Communication: Evidence from a Field Test," Marketing Science, INFORMS, vol. 28(4), pages 721-739, 07-08.
    4. Liye Ma & Baohong Sun & Sunder Kekre, 2015. "The Squeaky Wheel Gets the Grease—An Empirical Analysis of Customer Voice and Firm Intervention on Twitter," Marketing Science, INFORMS, vol. 34(5), pages 627-645, September.
    5. Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2011. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Management Science, INFORMS, vol. 57(8), pages 1485-1509, August.
    6. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    7. Anonymous, 2013. "Introduction to the Issue," Journal of Wine Economics, Cambridge University Press, vol. 8(3), pages 243-243, December.
    8. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    9. Smith, Andrew N. & Fischer, Eileen & Yongjian, Chen, 2012. "How Does Brand-related User-generated Content Differ across YouTube, Facebook, and Twitter?," Journal of Interactive Marketing, Elsevier, vol. 26(2), pages 102-113.
    10. Xiaoqing Wang & Brian S. Butler & Yuqing Ren, 2013. "The Impact of Membership Overlap on Growth: An Ecological Competition View of Online Groups," Organization Science, INFORMS, vol. 24(2), pages 414-431, April.
    11. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    12. Yinlong Zhang & Lawrence Feick & Vikas Mittal, 2014. "How Males and Females Differ in Their Likelihood of Transmitting Negative Word of Mouth," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 40(6), pages 1097-1108.
    13. Xianghua Lu & Sulin Ba & Lihua Huang & Yue Feng, 2013. "Promotional Marketing or Word-of-Mouth? Evidence from Online Restaurant Reviews," Information Systems Research, INFORMS, vol. 24(3), pages 596-612, September.
    14. Johanna Gummerus & Veronica Liljander & Emil Weman & Minna Pihlström, 2012. "Customer engagement in a Facebook brand community," Management Research Review, Emerald Group Publishing Limited, vol. 35(9), pages 857-877, August.
    15. Anonymous, 2013. "Introduction to the Issue," Journal of Wine Economics, Cambridge University Press, vol. 8(2), pages 129-130, November.
    16. Dokyun Lee & Kartik Hosanagar & Harikesh S. Nair, 2018. "Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook," Management Science, INFORMS, vol. 64(11), pages 5105-5131, November.
    17. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    18. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
    19. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
    20. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    21. Steven L. Johnson & Hani Safadi & Samer Faraj, 2015. "The Emergence of Online Community Leadership," Information Systems Research, INFORMS, vol. 26(1), pages 165-187, March.
    22. Brodie, Roderick J. & Ilic, Ana & Juric, Biljana & Hollebeek, Linda, 2013. "Consumer engagement in a virtual brand community: An exploratory analysis," Journal of Business Research, Elsevier, vol. 66(1), pages 105-114.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Kunpeng Zhang & Wendy Moe, 2021. "Measuring Brand Favorability Using Large-Scale Social Media Data," Information Systems Research, INFORMS, vol. 32(4), pages 1128-1139, December.
    2. Shan, Wei & Qiao, Tong & Zhang, Mingli, 2020. "Getting more resources for better performance: The effect of user-owned resources on the value of user-generated content," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    3. Shengsheng Xiao & Yi‐Chun (Chad) Ho & Hai Che, 2021. "Building the Momentum: Information Disclosure and Herding in Online Crowdfunding," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 3213-3230, September.
    4. Warut Khern-am-nuai & Hossein Ghasemkhani & Dandan Qiao & Karthik Kannan, 2024. "The Impact of Online Q&As on Product Sales: The Case of Amazon Answer," Information Systems Research, INFORMS, vol. 35(2), pages 747-765, June.
    5. Changseung Yoo & Eunae Yoo & Lu (Lucy) Yan & Alfonso Pedraza-Martinez, 2024. "Speak with One Voice? Examining Content Coordination and Social Media Engagement During Disasters," Information Systems Research, INFORMS, vol. 35(2), pages 551-569, June.
    6. Myoung-Jin Chae, 2021. "Driving Consumer Engagement through Diverse Calls to Action in Corporate Social Responsibility Messages on Social Media," Sustainability, MDPI, vol. 13(7), pages 1-22, March.
    7. Wolfgang Ketter & Karsten Schroer & Konstantina Valogianni, 2023. "Information Systems Research for Smart Sustainable Mobility: A Framework and Call for Action," Information Systems Research, INFORMS, vol. 34(3), pages 1045-1065, September.
    8. Wang, Fei & Xu, Haifeng & Hou, Ronglin & Zhu, Zhen, 2023. "Designing marketing content for social commerce to drive consumer purchase behaviors: A perspective from speech act theory," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    9. Gordon Burtch & Edward McFowland III & Mochen Yang & Gediminas Adomavicius, 2023. "EnsembleIV: Creating Instrumental Variables from Ensemble Learners for Robust Statistical Inference," Papers 2303.02820, arXiv.org, revised Dec 2024.
    10. Enrique Bigne & Carla Ruiz & Carmen Perez-Cabañero & Antonio Cuenca, 2023. "Are customer star ratings and sentiments aligned? A deep learning study of the customer service experience in tourism destinations," Service Business, Springer;Pan-Pacific Business Association, vol. 17(1), pages 281-314, March.
    11. Osei-Frimpong, Kofi & McLean, Graeme & Islam, Nazrul & Appiah Otoo, Brigid, 2022. "What drives me there? The interplay of socio-psychological gratification and consumer values in social media brand engagement," Journal of Business Research, Elsevier, vol. 146(C), pages 288-307.
    12. Yu-Kai Lin & Arun Rai & Yukun Yang, 2022. "Information Control for Creator Brand Management in Subscription-Based Crowdfunding," Information Systems Research, INFORMS, vol. 33(3), pages 846-866, September.
    13. Zhao, Lu & Zhang, Mingli & Ming, Yaxin & Niu, Tao & Wang, Yu, 2023. "The effect of image richness on customer engagement: Evidence from Sina Weibo," Journal of Business Research, Elsevier, vol. 154(C).
    14. Wei, Zihan & Zhang, Mingli & Qiao, Tong, 2022. "Effect of personal branding stereotypes on user engagement on short-video platforms," Journal of Retailing and Consumer Services, Elsevier, vol. 69(C).
    15. Menghan Sun & Jichang Zhao, 2020. "How do online consumers review negatively?," Papers 2004.13463, arXiv.org.
    16. Vuković, Dijana & Kocijan, Samanta & Globočnik Žunac, Ana, 2023. "Contemporary Communication Model of Consumer Behaviour of Generation C," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2023), Hybrid Conference, Dubrovnik, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Hybrid Conference, Dubrovnik, Croatia, 4-6 September, 2023, pages 329-340, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    17. Lu, Lin & Xu, Pei & Wang, Yen-Yao & Wang, Yu, 2023. "Measuring service quality with text analytics: Considering both importance and performance of consumer opinions on social and non-social online platforms," Journal of Business Research, Elsevier, vol. 169(C).
    18. Sunghun Chung & Animesh Animesh & Kunsoo Han & Alain Pinsonneault, 2020. "Financial Returns to Firms’ Communication Actions on Firm-Initiated Social Media: Evidence from Facebook Business Pages," Information Systems Research, INFORMS, vol. 31(1), pages 258-285, March.
    19. Bei Yan & Feng Mai & Chaojiang Wu & Rui Chen & Xiaolin Li, 2024. "A Computational Framework for Understanding Firm Communication During Disasters," Information Systems Research, INFORMS, vol. 35(2), pages 590-608, June.
    20. Ramah Al Balawi & Yuheng Hu & Liangfei Qiu, 2023. "Brand Crisis and Customer Relationship Management on Social Media: Evidence from a Natural Experiment from the Airline Industry," Information Systems Research, INFORMS, vol. 34(2), pages 442-462, June.
    21. Colmekcioglu, Nazan & Marvi, Reza & Foroudi, Pantea & Okumus, Fevzi, 2022. "Generation, susceptibility, and response regarding negativity: An in-depth analysis on negative online reviews," Journal of Business Research, Elsevier, vol. 153(C), pages 235-250.
    22. Jiaqi Wang & Peng Zou & Bo Yu, 2024. "How online exposure to nature affects customer engagement: Evidence from Sina Weibo," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-17, December.
    23. Tianshu Sun & Siva Viswanathan & Elena Zheleva, 2021. "Creating Social Contagion Through Firm-Mediated Message Design: Evidence from a Randomized Field Experiment," Management Science, INFORMS, vol. 67(2), pages 808-827, February.
    24. van der Harst, Jesse Pieter & Angelopoulos, Spyros, 2024. "Less is more: Engagement with the content of social media influencers," Journal of Business Research, Elsevier, vol. 181(C).
    25. Shimi Naurin Ahmad & Michel Laroche, 2023. "Extracting marketing information from product reviews: a comparative study of latent semantic analysis and probabilistic latent semantic analysis," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(4), pages 662-676, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Angela Aerry Choi & Daegon Cho & Dobin Yim & Jae Yun Moon & Wonseok Oh, 2019. "When Seeing Helps Believing: The Interactive Effects of Previews and Reviews on E-Book Purchases," Information Systems Research, INFORMS, vol. 30(4), pages 1164-1183, December.
    2. Dominik Gutt & Jürgen Neumann & Steffen Zimmermann & Dennis Kundisch & Jianqing Chen, 2018. "Design of Review Systems - A Strategic Instrument to shape Online Review Behavior and Economic Outcomes," Working Papers Dissertations 42, Paderborn University, Faculty of Business Administration and Economics.
    3. Young Kwark & Gene Moo Lee & Paul A. Pavlou & Liangfei Qiu, 2021. "On the Spillover Effects of Online Product Reviews on Purchases: Evidence from Clickstream Data," Information Systems Research, INFORMS, vol. 32(3), pages 895-913, September.
    4. Mochen Yang & Gediminas Adomavicius & Gordon Burtch & Yuqing Rena, 2018. "Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining," Information Systems Research, INFORMS, vol. 29(1), pages 4-24, March.
    5. Jorge Mejia & Shawn Mankad & Anandasivam Gopal, 2019. "A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections," Information Systems Research, INFORMS, vol. 30(4), pages 1363-1386, December.
    6. Bertschek, Irene & Kesler, Reinhold, 2022. "Let the user speak: Is feedback on Facebook a source of firms’ innovation?," Information Economics and Policy, Elsevier, vol. 60(C).
    7. Tingting Song & Jinghua Huang & Yong Tan & Yifan Yu, 2019. "Using User- and Marketer-Generated Content for Box Office Revenue Prediction: Differences Between Microblogging and Third-Party Platforms," Service Science, INFORMS, vol. 30(1), pages 191-203, March.
    8. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    9. Nigam, Nirjhar & Benetti, Cristiane & Johan, Sofia A., 2020. "Digital start-up access to venture capital financing: What signals quality?," Emerging Markets Review, Elsevier, vol. 45(C).
    10. Heeseung Andrew Lee & Angela Aerry Choi & Tianshu Sun & Wonseok Oh, 2021. "Reviewing Before Reading? An Empirical Investigation of Book-Consumption Patterns and Their Effects on Reviews and Sales," Information Systems Research, INFORMS, vol. 32(4), pages 1368-1389, December.
    11. 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.
    12. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    13. Natalia Levina & Manuel Arriaga, 2014. "Distinction and Status Production on User-Generated Content Platforms: Using Bourdieu’s Theory of Cultural Production to Understand Social Dynamics in Online Fields," Information Systems Research, INFORMS, vol. 25(3), pages 468-488, September.
    14. Yabing Jiang & Hong Guo, 2012. "Design of Consumer Review Systems and Product Pricing," Working Papers 12-10, NET Institute.
    15. Tajvidi, Mina & Richard, Marie-Odile & Wang, YiChuan & Hajli, Nick, 2020. "Brand co-creation through social commerce information sharing: The role of social media," Journal of Business Research, Elsevier, vol. 121(C), pages 476-486.
    16. Pei-Yu Chen & Yili Hong & Ying Liu, 2018. "The Value of Multidimensional Rating Systems: Evidence from a Natural Experiment and Randomized Experiments," Management Science, INFORMS, vol. 64(10), pages 4629-4647, October.
    17. Weijia (Daisy) Dai & Ginger Jin & Jungmin Lee & Michael Luca, 2018. "Aggregation of consumer ratings: an application to Yelp.com," Quantitative Marketing and Economics (QME), Springer, vol. 16(3), pages 289-339, September.
    18. Gordon Burtch & Anindya Ghose & Sunil Wattal, 2013. "An Empirical Examination of the Antecedents and Consequences of Contribution Patterns in Crowd-Funded Markets," Information Systems Research, INFORMS, vol. 24(3), pages 499-519, September.
    19. Yanni Ping & Chelsey Hill & Yun Zhu & Jorge Fresneda, 2023. "Antecedents and consequences of the key opinion leader status: an econometric and machine learning approach," Electronic Commerce Research, Springer, vol. 23(3), pages 1459-1484, September.
    20. Vasu Unnava & Ashwin Aravindakshan, 2021. "How does consumer engagement evolve when brands post across multiple social media?," Journal of the Academy of Marketing Science, Springer, vol. 49(5), pages 864-881, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orisre:v:30:y:2019:i:3:p:839-855. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.