Data Mining Virtual Reference Chats

dc.date.accessioned2018-08-10T16:11:14Z
dc.date.available2018-08-10T16:11:14Z
dc.date.issued2017-03-07
dc.description.abstractFrom surveying the literature, most chat transcript analysis for academic libraries has been based on sampling. This project departs from that approach. Three years of raw data (15,441 chat transcripts) from LibraryH3lp was examined to better understand user experience. Open and proprietary software was used to text mine, process, and analyze the transcripts to identify and visualize patterns. Using this “big data” provides a window into unique community needs and has measurable applications to web technology, reference, and assessment.
dc.identifier.citationFerrance, C., Lam, M. and Polchow, M. Data Mining Virtual Reference Chats. Washington Research Library Consortium Annual Meeting, Washington, D.C. 7 March, 2017.
dc.identifier.urihttps://hdl.handle.net/1920/11104
dc.language.isoen_US
dc.rightsAttribution 3.0 United States
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/us/
dc.subjectResearch Subject Categories::SOCIAL SCIENCES
dc.titleData Mining Virtual Reference Chats
dc.typePresentation

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