Lariat: A Visual Analytics Tool for Social Media Researchers to Explore Twitter Datasets

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dc.contributor.authorChen, Nan-Chen
dc.contributor.authorBrooks, Michael
dc.contributor.authorKocielnik, Rafal
dc.contributor.authorHong, Sungsoo (Ray)
dc.contributor.authorSmith, Jeff
dc.contributor.authorLin, Sanny
dc.contributor.authorQu, Zening
dc.contributor.authorAragon, Cecilia
dc.date.accessioned2016-12-29T00:46:25Z
dc.date.available2016-12-29T00:46:25Z
dc.date.issued2017-01-04
dc.description.abstractOnline social data is potentially a rich source of insight into human behavior, but the sheer size of these datasets requires specialized tools to facilitate social media research. Visual analytics tools are one promising approach, but calls have been made for more in-depth studies in specific application domains to contribute to the design of such tools. We conducted a formative study to better understand the needs of social media researchers, and created Lariat, a visual analytics tool that facilitates exploratory data analysis through integrated grouping and visualization of social media data. The design of Lariat was informed by the results of the formative study and sensemaking theory, both indicating that the exploratory processes require search, comparison, verification, and iterative refinement. Based on our results and the evaluation of Lariat, we identify a number of design implications for future visual analytics tools in this domain.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2017.228
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41382
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectsocial media
dc.subjectuser research
dc.subjectvisual analytics
dc.subjectvisual exploration
dc.subjectvisualization
dc.titleLariat: A Visual Analytics Tool for Social Media Researchers to Explore Twitter Datasets
dc.typeConference Paper
dc.type.dcmiText

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