Brenda Starr at SemEval-2019 Task 4: Hyperpartisan News Detection

no code implementations • SEMEVAL 2019 • Olga Papadopoulou, Giorgos Kordopatis-Zilos, Markos Zampoglou, Symeon Papadopoulos, Yiannis Kompatsiaris

In the effort to tackle the challenge of Hyperpartisan News Detection, i. e., the task of deciding whether a news article is biased towards one party, faction, cause, or person, we experimented with two systems: i) a standard supervised learning approach using superficial text and bag-of-words features from the article title and body, and ii) a deep learning system comprising a four-layer convolutional neural network and max-pooling layers after the embedding layer, feeding the consolidated features to a bi-directional recurrent neural network.

TOTEMSS: Topic-based, Temporal Sentiment Summarisation for Twitter

no code implementations • IJCNLP 2017 • Bo Wang, Maria Liakata, Adam Tsakalidis, Spiros Georgakopoulos Kolaitis, Symeon Papadopoulos, Lazaros Apostolidis, Arkaitz Zubiaga, Rob Procter, Yiannis Kompatsiaris

We present a system for time sensitive, topic based summarisation of the sentiment around target entities and topics in collections of tweets.

Opinion Mining Sentiment Analysis

Bridge Bounding: A Local Approach for Efficient Community Discovery in Complex Networks

1 code implementation • 5 Feb 2009 • Symeon Papadopoulos, Andre Skusa, Athena Vakali, Yiannis Kompatsiaris, Nadine Wagner

There are numerous techniques adopting a global perspective to the community detection problem, i. e. they operate on the complete network structure, thus being computationally expensive and hard to apply in a streaming manner.

Data Analysis, Statistics and Probability Physics and Society