Combining behaviors and demographics to segment online audiences: Experiments with a youtube channel

Bernard J. Jansen, Soon Gyo Jung, Joni Salminen, Jisun An, Haewoon Kwak

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Social media channels with audiences in the millions are increasingly common. Efforts at segmenting audiences for populations of these sizes can result in hundreds of audience segments, as the compositions of the overall audiences tend to be complex. Although understanding audience segments is important for strategic planning, tactical decision making, and content creation, it is unrealistic for human decision makers to effectively utilize hundreds of audience segments in these tasks. In this research, we present efforts at simplifying the segmentation of audience populations to increase their practical utility. Using millions of interactions with hundreds of thousands of viewers with an organization’s online content collection, we first isolate the maximum number of audience segments, based on behavioral profiling, and then demonstrate a computational approach of using non-negative matrix factorization to reduce this number to 42 segments that are both impactful and representative segments of the overall population. Initial results are promising, and we present avenues for future research leveraging our approach.

Original languageEnglish (US)
Title of host publicationInternet Science - 5th International Conference, INSCI 2018, Proceedings
EditorsSvetlana S. Bodrunova
PublisherSpringer Verlag
Number of pages13
ISBN (Print)9783030014360
StatePublished - 2018
Event5th International Conference on Internet Science, INSCI 2018 - St. Petersburg, Russian Federation
Duration: Oct 24 2018Oct 26 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11193 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other5th International Conference on Internet Science, INSCI 2018
Country/TerritoryRussian Federation
CitySt. Petersburg

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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