Search Results for author:
Found 7 papers, 2 papers with code
Diversity matters: Robustness of bias measurements in Wikidata
With the widespread use of knowledge graphs (KG) in various automated AI systems and applications, it is very important to ensure that information retrieval algorithms leveraging them are free from societal biases.
Sentiment Analysis: Predicting Yelp Scores
In this work, we predict the sentiment of restaurant reviews based on a subset of the Yelp Open Dataset.
Quality change: norm or exception? Measurement, Analysis and Detection of Quality Change in Wikipedia
To the best of our knowledge, this is the first work that rigorously explores English Wikipedia article quality life cycle from the perspective of quality indicators and provides a novel unsupervised page level approach to detect quality switch, which can help in automatic content monitoring in Wikipedia thus contributing significantly to the CSCW community.
OPAD: An Optimized Policy-based Active Learning Framework for Document Content Analysis
We propose novel rewards to account for class imbalance and user feedback in the annotation interface, to improve the active learning method.
When expertise gone missing: Uncovering the loss of prolific contributors in Wikipedia
Success of planetary-scale online collaborative platforms such as Wikipedia is hinged on active and continued participation of its voluntary contributors.
EmpathBERT: A BERT-based Framework for Demographic-aware Empathy Prediction
Affect preferences vary with user demographics, and tapping into demographic information provides important cues about the users' language preferences.
Goal-driven Command Recommendations for Analysts
With this assumption, we would like to assist the analytics process of a user through command recommendations.
