TY - GEN
T1 - News Kaleidoscope
T2 - 15th IEEE Pacific Visualization Symposium, PacificVis 2022
AU - Mishra, Aditi
AU - Ginjpalli, Shashank
AU - Bryan, Chris
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - When a newsworthy event occurs, media articles that report on the event can vary widely-a concept known as coverage diversity. To help investigate coverage diversity in event reporting, we de-velop a visual analytics system called News Kaleidoscope. News Kaleidoscope combines several backend language processing techniques with a coordinated visualization interface. Notably, News Kaleidoscope is tailored for visualization non-experts, and adopts an analytic workflow based around subselection analysis, whereby second-level features of articles are extracted to provide a more detailed and nuanced analysis of coverage diversity. To robustly evaluate News Kaleidoscope, we conduct a trio of user studies. (1) A study with news experts assesses the insights promoted for our targeted journalism-savvy users. (2) A follow-up study with news novices assesses the overall system and the specific insights pro-moted for journalism-agnostic users. (3) Based on identified system limitations in these two studies, we refine News Kaleidoscope's design and conduct a third study to validate these improvements. Results indicate that, for both news novice and experts, News Kalei-doscope supports an effective, task-driven workflow for analyzing the diversity of news coverage about events, though journalism expertise has a significant influence on the user's insights and take-aways. Our insights developing and evaluating News Kaleidoscope can aid future tools that combine visualization with natural language processing to analyze coverage diversity in news event reporting.
AB - When a newsworthy event occurs, media articles that report on the event can vary widely-a concept known as coverage diversity. To help investigate coverage diversity in event reporting, we de-velop a visual analytics system called News Kaleidoscope. News Kaleidoscope combines several backend language processing techniques with a coordinated visualization interface. Notably, News Kaleidoscope is tailored for visualization non-experts, and adopts an analytic workflow based around subselection analysis, whereby second-level features of articles are extracted to provide a more detailed and nuanced analysis of coverage diversity. To robustly evaluate News Kaleidoscope, we conduct a trio of user studies. (1) A study with news experts assesses the insights promoted for our targeted journalism-savvy users. (2) A follow-up study with news novices assesses the overall system and the specific insights pro-moted for journalism-agnostic users. (3) Based on identified system limitations in these two studies, we refine News Kaleidoscope's design and conduct a third study to validate these improvements. Results indicate that, for both news novice and experts, News Kalei-doscope supports an effective, task-driven workflow for analyzing the diversity of news coverage about events, though journalism expertise has a significant influence on the user's insights and take-aways. Our insights developing and evaluating News Kaleidoscope can aid future tools that combine visualization with natural language processing to analyze coverage diversity in news event reporting.
KW - Human-centered computing-Visualization-Visu-alization techniques-Treemaps
KW - Human-centered computing-Visualization-Visualization design and evaluation methods
UR - http://www.scopus.com/inward/record.url?scp=85132422028&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85132422028&partnerID=8YFLogxK
U2 - 10.1109/PacificVis53943.2022.00022
DO - 10.1109/PacificVis53943.2022.00022
M3 - Conference contribution
AN - SCOPUS:85132422028
T3 - IEEE Pacific Visualization Symposium
SP - 131
EP - 140
BT - Proceedings - 2022 IEEE 15th Pacific Visualization Symposium, PacificVis 2022
PB - IEEE Computer Society
Y2 - 11 April 2022 through 14 April 2022
ER -