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Noninfluentials and information dissemination in the microblogging community

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Abstract

Firms are increasingly focusing on understanding and managing their social media strategies in order to create discussions and optimize the spread of news in their communities. Most prior studies on information dissemination have mainly focused on the roles of influentials but ignored the essential for noninfluentials. To fill this gap, this paper takes a holistic view of the information dissemination process and investigates how the participation of both influentials and noninfluentials plays a role in affecting the volume and sentiment of microblogs, which are precursors to raise awareness and attraction for brands. To test our hypotheses, we build a novel econometric model and apply it to a dataset collected from the popular microblogging site Twitter. We have the following main results: (1) back-and-forth-type discussions and retweets are effective in generating awareness and positive attractiveness; (2) influentials or mavens (who have many followers but seldom follow others) help generate initial sparks toward microblogging, but during the cascading periods, the noninfluentials play an important role in driving the conversations; and (3) new users who gradually join the discussions also help increase awareness, although they may not generate a positive sentiment. Our results provide important implications for mediating consumer interactions and firms’ marketing strategies.

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Notes

  1. https://about.twitter.com/company.

  2. In his book, Gladwell describes three kinds of people: connectors, mavens, and salesmen. To apply his idea in the microblogging context, we use the word “negotiators” instead of “salesmen” to explicitly emphasize the discussions and persuasions going on when people post microblogs. This is in line with what Gladwell says on page 80: “What happens when two people talk? That is really the basic question here, because that’s the basic context in which all persuasion takes place. We know that people talk back and forth.”.

  3. http://advertising.twitter.com/2013/04/Twitter-Ads-now-generally-available-for-US-users.html.

  4. http://venturebeat.com/2015/02/03/y-combinator-backed-ebrandvalue-wants-to-show-social-medias-impact-on-your-sales-in-real-time/.

  5. Due to the quota limit imposed by the Twitter Search API, we refrain from collecting the news articles mentioned in all microblogs returned in the query results. If more computing resources were available (e.g., more computers with unique IP addresses), one can expand the sample size by including news articles appearing in all microblogs in the query results.

  6. A platform is a set of subsystems and interfaces that form a common structure from which a stream of derivative products can be efficiently developed and produced [54, 54].

  7. For example, according to a recent campaign, a firm was promoting the success of the results of a Twitter campaign: The campaign reached 3,628,525 users on Twitter with a 1.24% average click-through rate and generated an 8.0c effective cost per click. Increasing the impact of such campaigns, lowering the cost, and increasing the awareness are possible using our model.

  8. http://www.readwriteweb.com/archives/who_uses_social_networks_and_what_are_they_like_part_1.php.

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Authors and Affiliations

  1. School of Business, Ozyegin University, Istanbul, Turkey

    Tolga Akcura

  2. Krannert School of Management, Purdue University, West Lafayette, IN, USA

    Kemal Altinkemer

  3. Department of Information Systems, College of Business, City University of Hong Kong, Kowloon Tong, Hong Kong

    Hailiang Chen

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  1. Tolga Akcura
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  2. Kemal Altinkemer
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  3. Hailiang Chen
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Correspondence to Kemal Altinkemer.

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The author thanks Tubitak (#111K476) for sponsorship of this research

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Akcura, T., Altinkemer, K. & Chen, H. Noninfluentials and information dissemination in the microblogging community. Inf Technol Manag 19, 89–106 (2018). https://doi.org/10.1007/s10799-017-0274-z

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