Map** online hate: A scientometric analysis on research trends and hotspots in research on online hate

A Waqas, J Salminen, S Jung, H Almerekhi, BJ Jansen - PloS one, 2019‏ - journals.plos.org
Internet and social media participation open doors to a plethora of positive opportunities for
the general public. However, in addition to these positive aspects, digital technology also …

Toward a perspectivist turn in ground truthing for predictive computing

F Cabitza, A Campagner, V Basile - … of the AAAI Conference on Artificial …, 2023‏ - ojs.aaai.org
Abstract Most current Artificial Intelligence applications are based on supervised Machine
Learning (ML), which ultimately grounds on data annotated by small teams of experts or …

DEPTWEET: A typology for social media texts to detect depression severities

M Kabir, T Ahmed, MB Hasan, MTR Laskar… - Computers in Human …, 2023‏ - Elsevier
Mental health research through data-driven methods has been hindered by a lack of
standard typology and scarcity of adequate data. In this study, we leverage the clinical …

Detecting pain points from user-generated social media posts using machine learning

J Salminen, M Mustak, J Corporan… - Journal of …, 2022‏ - journals.sagepub.com
Artificial intelligence, particularly machine learning, carries high potential to automatically
detect customers' pain points, which is a particular concern the customer expresses that the …

Topic-driven toxicity: Exploring the relationship between online toxicity and news topics

J Salminen, S Sengün, J Corporan, S Jung, BJ Jansen - PloS one, 2020‏ - journals.plos.org
Hateful commenting, also known as 'toxicity', frequently takes place within news stories in
social media. Yet, the relationship between toxicity and news topics is poorly understood. To …

Sentiment analysis on twitter for the major German parties during the 2021 German federal election

T Schmidt, J Fehle, M Weissenbacher… - Proceedings of the …, 2022‏ - epub.uni-regensburg.de
We present the results of a project performing sentiment analysis on tweets from German
politicians and party accounts for the 2021 German federal election. We collected over …

Online hate ratings vary by extremes: A statistical analysis

J Salminen, H Almerekhi, AM Kamel, S Jung… - Proceedings of the …, 2019‏ - dl.acm.org
Analyzing 5,665 crowd ratings on 1,133 social media comments, we find that individuals
tend to agree on the extremes of a hate rating scale more than in the middle when …

[HTML][HTML] PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits

H Almerekhi, H Kwak, J Salminen, BJ Jansen - Data and Information …, 2022‏ - Elsevier
Promoting healthy discourse on community-based online platforms like Reddit can be
challenging, especially when conversations show ominous signs of toxicity. Therefore, in …

Four types of toxic people: Characterizing online users' toxicity over time

R Mall, M Nagpal, J Salminen, H Almerekhi… - Proceedings of the 11th …, 2020‏ - dl.acm.org
Identifying types of online users' toxic behavior reveals important insights from social media
interactions, including whether a user becomes “radicalized”(more toxic) or “pacified”(less …

Crowdsourcing subjective annotations using pairwise comparisons reduces bias and error compared to the majority-vote method

H Narimanzadeh, A Badie-Modiri, IG Smirnova… - Proceedings of the …, 2023‏ - dl.acm.org
How to better reduce measurement variability and bias introduced by subjectivity in
crowdsourced labelling remains an open question. We introduce a theoretical framework for …