Towards understanding the lifespan and spread of ideas: Epidemiological modeling of participation on twitter

Sai Santosh Sasank Peri, Angela Liegey Dougall, Bodong Chen, George Siemens

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

Abstract

How ideas develop and evolve is a topic of interest for educators. By understanding this process, designers and educators are better able to support and guide collaborative learning activities. This paper presents an application of our Lifespan of an Idea framework to measure engagement patterns among individuals in communal socio-technical spaces like Twitter. We correlated engagement with social participation, enabling the process of idea expression, spread, and evolution. Social participation leads to transmission of ideas from one individual to another and can be gauged in the same way as evaluating diseases. The temporal dynamics of the social participation can be modeled through the lens of epidemiological modeling. To test the plausibility of this framework, we investigated social participation on Twitter using the tweet posting patterns of individuals in three academic conferences and one long term chat space. We used a basic SIR epidemiological model, where the rate parameters were estimated through Euler's solutions to SIR model and non-linear least squares optimization technique. We discuss the differences in the social participation among individuals in these spaces based on their transition behavior into different categories of the SIR model. We also made inferences on how the total lifetime of these different twitter spaces affects the engagement among individuals. We conclude by discussing implications of this study and planned future research of refining the Lifespan of an Idea Framework.

Original languageEnglish (US)
Title of host publicationLAK 2020 Conference Proceedings - Celebrating 10 years of LAK
Subtitle of host publicationShaping the Future of the Field - 10th International Conference on Learning Analytics and Knowledge
PublisherAssociation for Computing Machinery
Pages197-202
Number of pages6
ISBN (Electronic)9781450377126
DOIs
StatePublished - Mar 23 2020
Event10th International Conference on Learning Analytics and Knowledge: Shaping the Future of the Field, LAK 2020 - Frankfurt, Germany
Duration: Mar 23 2020Mar 27 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference10th International Conference on Learning Analytics and Knowledge: Shaping the Future of the Field, LAK 2020
CountryGermany
CityFrankfurt
Period3/23/203/27/20

Keywords

  • Connectivism
  • Engagement Patterns
  • Epidemiology
  • Ideas
  • Knowledge Creation
  • Networked Learning

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