IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v67y2021i2p1026-1047.html
   My bibliography  Save this article

Competition for Attention in Online Social Networks: Implications for Seeding Strategies

Author

Listed:
  • Sarah Gelper

    (School of Industrial Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, Netherlands)

  • Ralf van der Lans

    (Department of Marketing, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong)

  • Gerrit van Bruggen

    (Department of Marketing, Rotterdam School of Management, Erasmus University, 3000 DR Rotterdam, Netherlands)

Abstract

Many firms try to leverage consumers’ interactions on social platforms as part of their communication strategies. However, information on online social networks only propagates if it receives consumers’ attention. This paper proposes a seeding strategy to maximize information propagation while accounting for competition for attention. The theory of exchange networks serves as the framework for identifying the optimal seeding strategy and recommends seeding people that have many friends, who, in turn, have only a few friends. There is little competition for the attention of those seeds’ friends, and these friends are therefore responsive to the messages they receive. Using a game-theoretic model, we show that it is optimal to seed people with the highest Bonacich centrality. Importantly, in contrast to previous seeding literature that assumed a fixed and nonnegative connectivity parameter of the Bonacich measure, we demonstrate that this connectivity parameter is negative and needs to be estimated. Two independent empirical validations using a total of 34 social media campaigns on two different large online social networks show that the proposed seeding strategy can substantially increase a campaign’s reach. The second study uses the activity network of messages exchanged to confirm that the effects are driven by competition for attention. This paper was accepted by Anandhi Bharadwaj, information systems.

Suggested Citation

  • Sarah Gelper & Ralf van der Lans & Gerrit van Bruggen, 2021. "Competition for Attention in Online Social Networks: Implications for Seeding Strategies," Management Science, INFORMS, vol. 67(2), pages 1026-1047, February.
  • Handle: RePEc:inm:ormnsc:v:67:y:2021:i:2:p:1026-1047
    DOI: 10.1287/mnsc.2019.3564
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/mnsc.2019.3564
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.2019.3564?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. Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
    2. Heiss, Florian & Winschel, Viktor, 2008. "Likelihood approximation by numerical integration on sparse grids," Journal of Econometrics, Elsevier, vol. 144(1), pages 62-80, May.
    3. Coralio Ballester & Antoni Calvó-Armengol & Yves Zenou, 2006. "Who's Who in Networks. Wanted: The Key Player," Econometrica, Econometric Society, vol. 74(5), pages 1403-1417, September.
    4. Sharad Goel & Ashton Anderson & Jake Hofman & Duncan J. Watts, 2016. "The Structural Virality of Online Diffusion," Management Science, INFORMS, vol. 62(1), pages 180-196, January.
    5. Avi Goldfarb & Catherine Tucker, 2011. "Online Display Advertising: Targeting and Obtrusiveness," Marketing Science, INFORMS, vol. 30(3), pages 389-404, 05-06.
    6. De Bruyn, Arnaud & Lilien, Gary L., 2008. "A multi-stage model of word-of-mouth influence through viral marketing," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 151-163.
    7. Abhijit Banerjee & Arun G Chandrasekhar & Esther Duflo & Matthew O Jackson, 2019. "Using Gossips to Spread Information: Theory and Evidence from Two Randomized Controlled Trials," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(6), pages 2453-2490.
    8. Avi Goldfarb & Catherine Tucker, 2011. "Rejoinder--Implications of "Online Display Advertising: Targeting and Obtrusiveness"," Marketing Science, INFORMS, vol. 30(3), pages 413-415, 05-06.
    9. Michael Braun & André Bonfrer, 2011. "Scalable Inference of Customer Similarities from Interactions Data Using Dirichlet Processes," Marketing Science, INFORMS, vol. 30(3), pages 513-531, 05-06.
    10. Sinan Aral & Paramveer S. Dhillon, 2018. "Social influence maximization under empirical influence models," Nature Human Behaviour, Nature, vol. 2(6), pages 375-382, June.
    11. Ravi Bapna & Akhmed Umyarov, 2015. "Do Your Online Friends Make You Pay? A Randomized Field Experiment on Peer Influence in Online Social Networks," Management Science, INFORMS, vol. 61(8), pages 1902-1920, August.
    12. Blume, Lawrence E. & Easley, David & Kleinberg, Jon & Tardos, Éva, 2009. "Trading networks with price-setting agents," Games and Economic Behavior, Elsevier, vol. 67(1), pages 36-50, September.
    13. Sinan Aral & Dylan Walker, 2011. "Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks," Management Science, INFORMS, vol. 57(9), pages 1623-1639, February.
    14. Sinan Aral & Dylan Walker, 2014. "Tie Strength, Embeddedness, and Social Influence: A Large-Scale Networked Experiment," Management Science, INFORMS, vol. 60(6), pages 1352-1370, June.
    15. Rishika Rishika & Ashish Kumar & Ramkumar Janakiraman & Ram Bezawada, 2013. "The Effect of Customers' Social Media Participation on Customer Visit Frequency and Profitability: An Empirical Investigation," Information Systems Research, INFORMS, vol. 24(1), pages 108-127, March.
    16. Phillip, Marissa V. & Suri, Rajneesh, 2004. "Impact of Gender Differences on the Evaluation of Promotional Emails," Journal of Advertising Research, Cambridge University Press, vol. 44(4), pages 360-368, December.
    17. Hinz, Oliver & Skiera, Bernd & Barrot, Christian & Becker, Jan, 2011. "Seeding Strategies for Viral Marketing: An Empirical Comparison," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56543, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    18. Ralf van der Lans & Gerrit van Bruggen & Jehoshua Eliashberg & Berend Wierenga, 2010. "A Viral Branching Model for Predicting the Spread of Electronic Word of Mouth," Marketing Science, INFORMS, vol. 29(2), pages 348-365, 03-04.
    19. Uzi Harush & Baruch Barzel, 2017. "Dynamic patterns of information flow in complex networks," Nature Communications, Nature, vol. 8(1), pages 1-11, December.
    20. Ganesh Iyer & Zsolt Katona, 2016. "Competing for Attention in Social Communication Markets," Management Science, INFORMS, vol. 62(8), pages 2304-2320, August.
    21. Aral, Sinan & Muchnik, Lev & Sundararajan, Arun, 2013. "Engineering social contagions: Optimal network seeding in the presence of homophily," Network Science, Cambridge University Press, vol. 1(2), pages 125-153, August.
    22. Peter Zubcsek & Miklos Sarvary, 2011. "Advertising to a social network," Quantitative Marketing and Economics (QME), Springer, vol. 9(1), pages 71-107, March.
    23. Hema Yoganarasimhan, 2012. "Impact of social network structure on content propagation: A study using YouTube data," Quantitative Marketing and Economics (QME), Springer, vol. 10(1), pages 111-150, March.
    24. Rik Pieters & Michel Wedel & Jie Zhang, 2007. "Optimal Feature Advertising Design Under Competitive Clutter," Management Science, INFORMS, vol. 53(11), pages 1815-1828, November.
    25. Yansong Hu & Christophe Van den Bulte, 2014. "Nonmonotonic Status Effects in New Product Adoption," Marketing Science, INFORMS, vol. 33(4), pages 509-533, July.
    26. Mauro Bampo & Michael T. Ewing & Dineli R. Mather & David Stewart & Mark Wallace, 2008. "The Effects of the Social Structure of Digital Networks on Viral Marketing Performance," Information Systems Research, INFORMS, vol. 19(3), pages 273-290, September.
    27. Duncan J. Watts & Peter Sheridan Dodds, 2007. "Influentials, Networks, and Public Opinion Formation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(4), pages 441-458, May.
    28. Kartik Hosanagar & Peng Han & Yong Tan, 2010. "Diffusion Models for Peer-to-Peer (P2P) Media Distribution: On the Impact of Decentralized, Constrained Supply," Information Systems Research, INFORMS, vol. 21(2), pages 271-287, June.
    29. Catherine Tucker, 2008. "Identifying Formal and Informal Influence in Technology Adoption with Network Externalities," Management Science, INFORMS, vol. 54(12), pages 2024-2038, December.
    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. Yin, Xicheng & Li, Jing & Si, Hongyun & Wu, Peng, 2024. "Attention marketing in fragmented entertainment: How advertising embedding influences purchase decision in short-form video apps," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    2. Seigner, Benedikt David Christian & Milanov, Hana & Lundmark, Erik & Shepherd, Dean A., 2023. "Tweeting like Elon? Provocative language, new-venture status, and audience engagement on social media," Journal of Business Venturing, Elsevier, vol. 38(2).
    3. Zhou, Meihua & Angelopoulos, Spyros & Ou, Carol & Liu, Hongwei & Liang, Zhouyang, 2023. "Optimization of dynamic product offerings on online marketplaces: A network theory perspective," Other publications TiSEM 75d71155-88bf-4ff7-aba1-9, Tilburg University, School of Economics and Management.
    4. Nejad, Mohammad G. & Amini, Mehdi, 2024. "Designing profitable seeding Programs: The effects of social network properties and consumer homophily," Journal of Business Research, Elsevier, vol. 173(C).

    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. Muller, Eitan & Peres, Renana, 2019. "The effect of social networks structure on innovation performance: A review and directions for research," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 3-19.
    2. Alex Chin & Dean Eckles & Johan Ugander, 2022. "Evaluating Stochastic Seeding Strategies in Networks," Management Science, INFORMS, vol. 68(3), pages 1714-1736, March.
    3. Qingliang Wang & Fred Miao & Giri Kumar Tayi & En Xie, 2019. "What makes online content viral? The contingent effects of hub users versus non–hub users on social media platforms," Journal of the Academy of Marketing Science, Springer, vol. 47(6), pages 1005-1026, November.
    4. Tianshu Sun & Sean J. Taylor, 2020. "Displaying things in common to encourage friendship formation: A large randomized field experiment," Quantitative Marketing and Economics (QME), Springer, vol. 18(3), pages 237-271, September.
    5. Shan Huang & Sinan Aral & Yu Jeffrey Hu & Erik Brynjolfsson, 2020. "Social Advertising Effectiveness Across Products: A Large-Scale Field Experiment," Marketing Science, INFORMS, vol. 39(6), pages 1142-1165, November.
    6. Pescher, Christian & Reichhart, Philipp & Spann, Martin, 2014. "Consumer Decision-making Processes in Mobile Viral Marketing Campaigns," Journal of Interactive Marketing, Elsevier, vol. 28(1), pages 43-54.
    7. Zhang, Honghong & Fam, Kim-Shyan & Goh, Tiong-Thye & Dai, Xin, 2018. "When are influentials equally influenceable? The strength of strong ties in new product adoption," Journal of Business Research, Elsevier, vol. 82(C), pages 160-170.
    8. Tavasoli, Ali & Shakeri, Heman & Ardjmand, Ehsan & Young, William A., 2021. "Incentive rate determination in viral marketing," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1169-1187.
    9. Samadi, Mohammadreza & Nikolaev, Alexander & Nagi, Rakesh, 2016. "A subjective evidence model for influence maximization in social networks," Omega, Elsevier, vol. 59(PB), pages 263-278.
    10. Liangfei Qiu & Zhan (Michael) Shi & Andrew B. Whinston, 2018. "Learning from Your Friends’ Check-Ins: An Empirical Study of Location-Based Social Networks," Information Systems Research, INFORMS, vol. 29(4), pages 1044-1061, December.
    11. Wang, Feng & Zhang, Xueting & Chen, Man & Zeng, Wei & Cao, Rong, 2022. "The influential paradox: Brand and deal content sharing by influencers in friendship networks," Journal of Business Research, Elsevier, vol. 150(C), pages 503-514.
    12. Yan Leng & Xiaowen Dong & Esteban Moro & Alex Pentland, 2024. "Long-Range Social Influence in Phone Communication Networks on Offline Adoption Decisions," Information Systems Research, INFORMS, vol. 35(1), pages 318-338, March.
    13. Moldovan, Sarit & Steinhart, Yael & Lehmann, Donald R., 2019. "Propagators, Creativity, and Informativeness: What Helps Ads Go Viral," Journal of Interactive Marketing, Elsevier, vol. 47(C), pages 102-114.
    14. Rishika Rishika & Jui Ramaprasad, 2019. "The Effects of Asymmetric Social Ties, Structural Embeddedness, and Tie Strength on Online Content Contribution Behavior," Management Science, INFORMS, vol. 65(7), pages 3398-3422, July.
    15. Sinan Aral & Dylan Walker, 2014. "Tie Strength, Embeddedness, and Social Influence: A Large-Scale Networked Experiment," Management Science, INFORMS, vol. 60(6), pages 1352-1370, June.
    16. Thomas Chesney, 2017. "The Cascade Capacity Predicts Individuals to Seed for Diffusion Through Social Networks," Systems Research and Behavioral Science, Wiley Blackwell, vol. 34(1), pages 51-61, January.
    17. Gandal, Neil & Bar-Gill, Sagit, 2017. "Online Exploration, Content Choice & Echo Chambers: An Experiment," CEPR Discussion Papers 11909, C.E.P.R. Discussion Papers.
    18. Hinz, Oliver & Schulze, Christian & Takac, Carsten, 2014. "New product adoption in social networks: Why direction matters," Journal of Business Research, Elsevier, vol. 67(1), pages 2836-2844.
    19. Haris Krijestorac & Rajiv Garg & Vijay Mahajan, 2020. "Cross-Platform Spillover Effects in Consumption of Viral Content: A Quasi-Experimental Analysis Using Synthetic Controls," Information Systems Research, INFORMS, vol. 31(2), pages 449-472, June.
    20. Jing Wang & Anocha Aribarg & Yves F. Atchadé, 2013. "Modeling Choice Interdependence in a Social Network," Marketing Science, INFORMS, vol. 32(6), pages 977-997, November.

    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:ormnsc:v:67:y:2021:i:2:p:1026-1047. 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.