Confidence levels for empirical research using twitter data: Extended abstract

Heng Xu, Nan Zhang

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

Abstract

Concerns of a "reproducibility crisis" in scientiffic research have become increasingly prevalent. .The field of meta science-the scientiffic study of science itself-is thriving and has examined the existence and prevalence of threats to reproducible and robust research in designed experiments or surveys. Nonetheless, largely missing are replication efforts devoted to examining empirical studies with "organic data"-e.g., data organically generated by ubiquitous sensors or mobile applications, twi.er feeds, click streams, etc. Given the growing popularity of using Twitter as the source of research data in psychology, we must take proper care of the data handling process if Twitter as a data source is to be a robust, reliable, and reproducible endeavor into the future. Our research studies scholarly publications in psychology to establish the conffidence (or the lack thereof) in their handling practices of Twitter data.

Original languageEnglish (US)
Title of host publicationProceedings of the Technology, Mind, and Society Conference, TechMindSociety 2018
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450354202
DOIs
StatePublished - Apr 5 2018
Event2018 Technology, Mind, and Society Conference, TechMindSociety 2018 - Washington, United States
Duration: Apr 5 2018Apr 7 2018

Publication series

NameACM International Conference Proceeding Series

Other

Other2018 Technology, Mind, and Society Conference, TechMindSociety 2018
CountryUnited States
CityWashington
Period4/5/184/7/18

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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    Xu, H., & Zhang, N. (2018). Confidence levels for empirical research using twitter data: Extended abstract. In Proceedings of the Technology, Mind, and Society Conference, TechMindSociety 2018 [a44] (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3183654.3183684