6.3 Moderators

  • Two key moderators when different WOM functions have a greater impact:

    • Communication audience:

    • Communication Channel

      • Written vs. oral
      • Identifiability: whether communicators are identifiable. (anonymously)
      • Audience salience: whether the audience is salient during communication (online communication, the audience is less salient).

Social motivation: why we share :(why_some_videos_go_viral_2015)

  • Impression management:

    • authority (e.g., “I want to demonstrate my knowledge”)
    • Social utility (e.g., this could be useful to my friends)
    • coolhunter (e.g., I want to be the first o tell my friends)
    • Zeitgeist (e.g., It’s about a current trend or event)
    • Conversation starting (e.g., I want to start an online conversation)
    • Self-expression (e.g., it says something about me)
    • Social good (e.g., It’s for a good cause, and I want to help”).
  • Information acquisition:

    • Opinion seeking (e.g., “I want to see what my friends think)
  • Social bonding:

    • Shared passion (e.g, “it lets me connect with my friends bout a shared interest)
    • Social in real life (e.g., it will help me socialize with my friends offline).

More frequent exposure to perceptually or conceptually related cues increases product accessibility and makes the product easier to process. In turn, this increased accessibility influences product evaluation and choice, which are found to vary directly with the frequency of exposure to conceptually related cues. These results support the hypothesis that conceptual priming effects can have a strong impact on real-world consumer judgment” (Berger and Fitzsimons 2008)

6.3.1 Tie Strength

(Peng et al. 2018)

  • the authors establish that a receiver is more likely to share content from a sender with whom they share more common followees, common followers, or common mutual followers even after accounting for other measures.

  • Assess the impact of network overlap across dyads on the level of content sharing in social platforms.

  • Network overlap is defined as:

    • Common followees

    • Common followers

    • Common mutual followers

  • Network overlap (similarly embeddedness or social cohesion ) can influence the sharing propensity :

    • A high number of common followers means that senders and receivers have similar interests and may have a similar propensity to share a common content

    • More common followers and common mutual followers meant that their followers share a similar interest. Hence a receiver thinks content is more suitable for her audience and has a higher propensity to share

    • A user may be less likely to share popular content because many others have already shared it

  • Used data on Twitter and Digg

  • Use dyadic hazard model

J. K. Lee and Kronrod (2020)

  • Consensus language: Words and expressions that imply widespread agreement among a group of people about a viewpoint, a product, or a conduct

  • The strength tie between the communicator and the receiver of WOM affects the interpretation and persuasiveness of consensus language.

  • When employing consensus language, weak links (e.g., distant friends, acquaintances) have more influence than strong ties, because weak relationships inspire views of a broader and more diversified group in agreement, signaling higher validity for the topic at hand.

  • For tie strength operationalization in the literature, see table 1 (p. 355)

  • Descriptive norms provide social proof 6.4.1 (i.e., social validation)

  • For the first experiment, the language of the message was too formal (p. 360). Hence, it’s more likely that the strong ties will become suspicious of the news, while weak ties might think it’s normal and click on it.

References

Berger, Jonah, and Gráinne Fitzsimons. 2008. “Dogs on the Street, Pumas on Your Feet: How Cues in the Environment Influence Product Evaluation and Choice.” Journal of Marketing Research 45 (1): 1–14. https://doi.org/10.1509/jmkr.45.1.1.
Lee, Jeffrey K., and Ann Kronrod. 2020. “The Strength of Weak-Tie Consensus Language.” Journal of Marketing Research 57 (2): 353–74. https://doi.org/10.1177/0022243720904957.
Peng, Jing, Ashish Agarwal, Kartik Hosanagar, and Raghuram Iyengar. 2018. “Network Overlap and Content Sharing on Social Media Platforms.” Journal of Marketing Research 55 (4): 571–85. https://doi.org/10.1509/jmr.14.0643.