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Ravi Vatrapu

Researcher at Copenhagen Business School

Publications -  178
Citations -  3243

Ravi Vatrapu is an academic researcher from Copenhagen Business School. The author has contributed to research in topics: Social media & Analytics. The author has an hindex of 26, co-authored 174 publications receiving 2749 citations. Previous affiliations of Ravi Vatrapu include Drexel University & IT University of Copenhagen.

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Journal ArticleDOI

Beyond threaded discussion: Representational guidance in asynchronous collaborative learning environments

TL;DR: Results show that users of knowledge maps created more hypotheses earlier in the experimental sessions and elaborated on them more than users of threaded discussions, suggesting that there was greater collaboration during the session.
Journal ArticleDOI

Off the wall political discourse: Facebook use in the 2008 U.S. presidential election

TL;DR: This paper examines two years of posts on the Facebook walls of the three major contenders for the U.S. Presidency in 2008 and analyzes participation patterns of usage along dimensions of breadth and frequency, and interpret them in terms of the concept of the "public sphere".
Proceedings ArticleDOI

Blockchain-based Personal Health Data Sharing System Using Cloud Storage

TL;DR: This research work proposes a conceptual design for sharing personal continuous-dynamic health data using blockchain technology supplemented by cloud storage to share the health-related information in a secure and transparent manner and introduces a data quality inspection module based on machine learning techniques to have control over data quality.
Journal Article

Culture and usability evaluation: the effects of culture in structured interviews

TL;DR: The results of the study empirically establish that culture significantly affects the efficacy of structured interviews during international user testing as discussed by the authors, and that participants found more usability problems and made more suggestions to an interviewer who was a member of the same culture than to the foreign (Anglo-American) interviewer.
Proceedings ArticleDOI

Breaking Bad: De-Anonymising Entity Types on the Bitcoin Blockchain Using Supervised Machine Learning

TL;DR: This paper presents a novel approach for reducing the anonymity of the Bitcoin Blockchain by using Supervised Machine Learning to predict the type of yet-unidentified entities, and finds that it can indeed predict thetype of a yet- unidentified entity.