EDBT 2026 Demo / reviewers in the wild / expert
Abu Saleh Md Noman
dblp:140/0358
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Collaborative and social computing · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing
sentiment analysis |
0.1 | 1 | 2019 | Techies Against Facebook: Understanding Negative Sentiment Toward Facebook via User Generated Content · CHI 2019 |
Methods — techniques the papers use, named apart from their topics
user-generated content analysis · 0.4qualitative coding · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Techies Against Facebook: Understanding Negative Sentiment Toward Facebook via User Generated ContentabstractResearchers have recognized the need to pay attention to negative aspects and non-use of social media services to uncover usage barriers and surface shortcomings of these systems. We contribute to these efforts by analyzing comments on posts related to Facebook on two blogs with a technically savvy readership: Slashdot and Schneier on Security. Our analysis indicates that technically savvy individuals exhibit notably large negative sentiment toward Facebook with nearly 45% of the 3,000 reader comments we coded expressing such views. Qualitative coding revealed Privacy and Security, User Experience, and Personal Disposition as key factors underlying the negative views. Our findings suggest that negative sentiment is an explicit higher level factor driving non-use practices. Further, we confirm several non-use practices reported in the literature and identify additional aspects connected to recent technological and societal developments. Our results demonstrate that analysis of user generated content can be useful for surfacing usage practices on a large scale. Abu Saleh Md Noman, Sanchari Das 0001, Sameer Patil 0001 |
CHI | 1 |