Dominik WurzerPhD student at the University of Edinburgh
- Publications -
Counteracting Novelty Decay in First Story Detection
In this paper we explore the impact of processing unbounded data streams on First Story Detection (FSD) accuracy. In particular, we study three diﬀerent types of FSD algorithms: comparison-based, LSH-based and k-term based FSD. Our experiments reveal for the ﬁrst time that the novelty score of all three algorithms decay over time. We explain why the decay is linked to the increased space saturation and negatively aﬀects detection accuracy. We provide a mathematical decay model, which allows compensating observed novelty scores by their expected decay. Our experiments show signiﬁcantly increased performance when counteracting the novelty score decay.
Spotting Information biases in Chinese and Western Media
Newswire and Social Media are the major sources of information in our time. While the topical demographic of Western Media was subjects of studies in the past, less is known about Chinese Media. In this paper, we apply event detection and tracking technology to examine the information overlap and diﬀerences between Chinese and Western – Traditional Media and Social Media. Our experiments reveal a biased interest of China towards the West, which becomes particularly apparent when comparing the interest in celebrities.
Spotting Rumors via Novelty Detection
Rumour detection is hard because the most accurate systems operate retrospectively, only recognizing rumours once they have collected repeated signals. By then the rumours might have already spread and caused harm. We introduce a new category of features based on novelty, tailored to detect rumours early on. To compensate for the absence of repeated signals, we make use of news wire as an additional data source. Unconfirmed (novel) information with respect to the news articles is considered as an indication of rumours. Additionally we introduce pseudo feedback, which assumes that documents that are similar to previous rumours, are more likely to also be a rumour. Comparison with other real-time approaches shows that novelty based features in conjunction with pseudo feedback perform significantly better, when detecting rumours instantly after their publication.