Extracting News Events from Microblogs

Twitter stream has become a large source of information for many people, but the magnitude of tweets and the noisy nature of its content have made harvesting the knowledge from Twitter a challenging task for researchers for a long time. Aiming at overcoming some of the main challenges of extracting the hidden information from tweet streams, this work proposes a new approach for real-time detection of news events from the Twitter stream. We divide our approach into three steps. The first step is to use a neural network or deep learning to detect news-relevant tweets from the stream. The second step is to apply a novel streaming data clustering algorithm to the detected news tweets to form news events. The third and final step is to rank the detected events based on the size of the event clusters and growth speed of the tweet frequencies. We evaluate the proposed system on a large, publicly available corpus of annotated news events from Twitter. As part of the evaluation, we compare our approach with a related state-of-the-art solution. Overall, our experiments and user-based evaluation show that our approach on detecting current (real) news events delivers a state-of-the-art performance

Performance Comparison of Turkish Web Pages Classification

Nowadays., web page classification is essential for efficient and fast search engines. There is an ever-increasing need for automatic classification techniques with higher classification accuracy. In this article., a performance comparison of existing Turkish language CNN models for web pages classification systems is performed. In more detail., the content of web pages is extracted first., then preprocessing steps that aim to detect the important parts and eliminate useless contents are used. Next., Bert word embedding is integrated to represent the texts by efficient numerical vectors. Finally., three state-of-the-art CNN models that fully support the Turkish language are investigated to find the best classifier. Overall., the three studied models obtained an acceptable performance while classifying the Turkish webpages., however., the third model was able to achieve slightly better than the other two models. © 2021 IEEE