Book ChapterDOI
Identification of Relevant Hashtags for Planned Events Using Learning to Rank
Sreekanth Madisetty,Maunendra Sankar Desarkar +1 more
- pp 82-99
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TLDR
This paper defines a set of features for (event, hashtag) pairs, and discusses ways to obtain these feature scores, and establishes the superiority of the method by performing detailed experiments on a large dataset containing multiple categories of events and related tweets.Abstract:
Lots of planned events (e.g. concerts, sports matches, festivals, etc.) keep happening across the world every day. In various applications like event recommendation, event reporting, etc. it might be useful to find user discussions related to such events from social media. Identification of event related hashtags can be useful for this purpose. In this paper, we focus on identifying the top hashtags related to a given event. We define a set of features for (event, hashtag) pairs, and discuss ways to obtain these feature scores. A linear aggregation of these scores is used to finally output a ranked list of top hashtags for the event. The aggregation weights of the features are obtained using a learning to rank algorithm. We establish the superiority of our method by performing detailed experiments on a large dataset containing multiple categories of events and related tweets.read more
Citations
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Journal ArticleDOI
A stacked convolutional neural network for detecting the resource tweets during a disaster
TL;DR: St stacking of Convolutional Neural Networks with traditional feature based classifiers is proposed for detecting the NAR tweets and the experimental results proved that the proposed model achieves the best accuracy compared to baseline methods.
Journal ArticleDOI
Research topics and trends of the hashtag recommendation domain
TL;DR: A review of existing works in the hashtag recommendation filed is presented, demonstrating that there are four evolved thematic areas in this research field, including “SIMILARITY”, “HASHTAG-RECOMMENDATION’,” “MACHINE-LEARNING” and “POPULARITY-PREDICTION”.
References
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