activity
20182026
most cited"HOT" ChatGPT: The promise of ChatGPT in detecting and discriminating hateful, offensive, and toxic comments on social media

87 citations · 377 across the 33 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.DL2022★ 3 cited

A Natural Language Processing Pipeline for Detecting Informal Data References in Academic Literature

Sara Lafia, Lizhou Fan, Libby Hemphill

Discovering authoritative links between publications and the datasets that they use can be a labor-intensive process. We introduce a natural language processing pipeline that retri…

cs.DL2022★ 10 cited

Subdivisions and Crossroads: Identifying Hidden Community Structures in a Data Archive's Citation Network

Sara Lafia, Lizhou Fan, Andrea Thomer +1

Data archives are an important source of high quality data in many fields, making them ideal sites to study data reuse. By studying data reuse through citation networks, we are abl…

cs.SI2022★ 3 cited

Leaders or Followers? A Temporal Analysis of Tweets from IRA Trolls

Siva K. Balasubramanian, Mustafa Bilgic, Aron Culotta +3

The Internet Research Agency (IRA) influences online political conversations in the United States, exacerbating existing partisan divides and sowing discord. In this paper we inves…

cs.DL2022★ 4 cited

Librarian-in-the-Loop: A Natural Language Processing Paradigm for Detecting Informal Mentions of Research Data in Academic Literature

Lizhou Fan, Sara Lafia, David Bleckley +3

Data citations provide a foundation for studying research data impact. Collecting and managing data citations is a new frontier in archival science and scholarly communication. How…

cs.DL2022★ 32 cited

The craft and coordination of data curation: complicating "workflow" views of data science

Andrea K. Thomer, Dharma Akmon, Jeremy York +5

Data curation is the process of making a dataset fit-for-use and archiveable. It is critical to data-intensive science because it makes complex data pipelines possible, makes studi…

cs.CY2022★ 19 cited

Remove, Reduce, Inform: What Actions do People Want Social Media Platforms to Take on Potentially Misleading Content?

Shubham Atreja, Libby Hemphill, Paul Resnick

To reduce the spread of misinformation, social media platforms may take enforcement actions against offending content, such as adding informational warning labels, reducing distrib…