Skip to main content
Log in

Exploring the attributes of influential users in social networks using association rule mining

  • Original Article
  • Published:
Social Network Analysis and Mining Aims and scope Submit manuscript

Abstract

Association rule mining discovers interesting patterns and meaningful connections between items or actions performed by users on social media platforms. These connections can provide valuable insights into user behavior, preferences, and interactions within the social media ecosystem. This study utilizes the association rule mining to identify Key attributes of influential individuals who can effectively influence others to actively participate in activities such as writing posts, answering questions, and sharing posted content on popular social news aggregation and discussion websites such as reddit.com. The research relies on user profiles and activity logs as data sources for analysis. The study’s findings include the observation that highly influential sharers often engage in regular content creation and sharing related to topics like entrepreneurship, personal development, and professional growth. Furthermore, it suggests that influential sharers are active during both business and prime times. In terms of specific dimensions of interest, it was found that women are more likely to be influenced by individuals who frequently write about personal growth. Similarly, the study highlights that teenagers have the most influence over their peers. Additionally, when considering the interplay of age and gender, it has been identified that adult males, especially, possess the ability to convince and influence other males. The insights gained from this study can prove valuable to marketers seeking to target specific individuals for effective social marketing campaigns.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. https://backlinko.com/reddit-users/ Accessed on 18–06-2023.

  2. https://github.com/cbuntain/redditResponseExtractor/ Accessed on 30–06-2023.

References

Download references

Author information

Authors and Affiliations

Authors

Contributions

The author confirms sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation.

Corresponding author

Correspondence to Mohammed Alghobiri.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Alghobiri, M. Exploring the attributes of influential users in social networks using association rule mining. Soc. Netw. Anal. Min. 13, 118 (2023). https://doi.org/10.1007/s13278-023-01118-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s13278-023-01118-4

Keywords

Navigation