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Getting Rid of Data
We are experiencing an amazing data-centered revolution. Incredible amounts of data are collected, integrated, and analyzed, leading to key breakthroughs in science and society. This well of knowledge, however, is at a great risk if we do not dispense ...
Transforming Pairwise Duplicates to Entity Clusters for High-quality Duplicate Detection
Duplicate detection algorithms produce clusters of database records, each cluster representing a single real-world entity. As most of these algorithms use pairwise comparisons, the resulting (transitive) clusters can be inconsistent: Not all records ...
Automated Selection and Quality Assessment of Primary Studies: A Systematic Literature Review
Researchers use systematic literature reviews (SLRs) to synthesize existing evidence regarding a research topic. While being an important means to condense knowledge, conducting an SLR requires a large amount of time and effort. Consequently, ...
Robustness of Word and Character N-gram Combinations in Detecting Deceptive and Truthful Opinions
Opinions in reviews about the quality of products or services can be important information for readers. Unfortunately, such opinions may include deceptive ones posted for some business reasons. To keep the opinions as a valuable and trusted source of ...
Experience: Managing Misinformation in Social Media—Insights for Policymakers from Twitter Analytics
Governance of misinformation is a serious concern in social media platforms. Based on experiences gathered from different case studies, we offer insights for the policymakers on managing misinformation in social media. These platforms are widely used ...
