Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41382

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

File SizeFormat 
paper0233.pdf475.53 kBAdobe PDFView/Open

Item Summary

Title: Lariat: A Visual Analytics Tool for Social Media Researchers to Explore Twitter Datasets
Authors: Chen, Nan-Chen
Brooks, Michael
Kocielnik, Rafal
Hong, Sungsoo (Ray)
Smith, Jeff
show 3 moreLin, Sanny
Qu, Zening
Aragon, Cecilia

show less
Keywords: social media
user research
visual analytics
visual exploration
visualization
Issue Date: 04 Jan 2017
Abstract: Online 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.
Pages/Duration: 10 pages
URI/DOI: http://hdl.handle.net/10125/41382
ISBN: 978-0-9981331-0-2
DOI: 10.24251/HICSS.2017.228
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Data Analytics and Data Mining for Social Media Minitrack



Items in ScholarSpace are protected by copyright, with all rights reserved, unless otherwise indicated.