Rezvaneh Rezapour

  • Citations Per Year
Learn More
We present novel research at the intersection of review mining and impact assessment of issue-focused information products, namely documentary films. We develop and evaluate a theoretically grounded classification schema, related codebook, corpus annotation, and prediction model for detecting multiple types of impact that documentaries can have on(More)
1:00 – 2:00 p.m.  Presentation Session I YESWORKFLOW: MORE PROVENANCE MILEAGE FROM HYBRID PROVENANCE MODELS AND QUERIES Bertram Ludäscher (presenter); joint work with Duc Vu, Qiwen Wang, Yang Cao, Qian Zhang, Timothy McPhillips ALL AND EACH: THE DYNAMICS OF SCALE IN DIGITAL HERITAGE CULTURES Rhiannon Bettivia INFORMED CONSENT AND CHEMICAL EXPOSURE FROM(More)
In this paper, we evaluate the predictability of tweets associated with controversial versus non-controversial topics. As a first step, we crowd-sourced the scoring of a predefined set of topics on a Likert scale from non-controversial to controversial. Our feature set entails and goes beyond sentiment features, e.g., by leveraging empathic language and(More)
The popularity and availability of Twitter as a service and a data source have fueled the interest in sentiment analysis. Previous research has shed light on the challenges that contextualizing effects and linguistic complexities pose for the accurate sentiment classification of tweets. We test the effect of adding manually-annotated, corpus-based hashtags(More)
  • 1