Hashtag Generation with Transfer Learning

Hashtag Healthcare: From Tweets to Mental Health Journals Using Deep Transfer Learning

As the popularity of social media platforms continues to rise, an ever-increasing amount of human communication and selfexpression takes place online. Most recent research has focused on mining social media for public user opinion about external entities such as product reviews or sentiment towards political news. However, less attention has been paid to analyzing users’ internalized thoughts a...

Learning Module Generation Transfer Parsing Runtime Trranslation Module SL Input TL Output Transfer Rules − Seed Generation − SVS Learning Process : Learning

Neural Paraphrase Generation using Transfer Learning

Progress in statistical paraphrase generation has been hindered for a long time by the lack of large monolingual parallel corpora. In this paper, we adapt the neural machine translation approach to paraphrase generation and perform transfer learning from the closely related task of entailment generation. We evaluate the model on the Microsoft Research Paraphrase (MSRP) corpus and show that the ...

Location-Aware Online Learning for Top-k Hashtag Recommendation

In this paper we investigate the problem of recommending Twitter hashtags for users with known GPS location, learning online from the stream of geo-tagged tweets. Our method learns the relevance of regions in a geographical hierarchy, combined with the local popularity of the hashtag. Unlike in typical collaborative filtering settings, trends and geolocation turns out to be more important than ...

Learning Emotion Indicators from Tweets: Hashtags, Hashtag Patterns, and Phrases

We present a weakly supervised approach for learning hashtags, hashtag patterns, and phrases associated with five emotions: AFFECTION, ANGER/RAGE, FEAR/ANXIETY, JOY, and SADNESS/DISAPPOINTMENT. Starting with seed hashtags to label an initial set of tweets, we train emotion classifiers and use them to learn new emotion hashtags and hashtag patterns. This process then repeats in a bootstrapping f...