Exploiting Emotional Knowledge from Emojis and Hashtags PyConHK 2018

Grasping other persons emotions or sentiments through texts is challenging even for humans sometimes. I bet you also have an experience that once you were reading someones message multiple times to figure out Is heshe upset? Or am I too sensitive? Despite the difficulties figuring out emotion or sentiment in texts is crucial nowadays due to our daily habit of using emails mobile messengers social media chats. An interesting question is can we teach machines to understand sentiment and emotions inside our texts? We introduce how to build a sentimentemotion analysis system by training deep learning models with a huge amount of tweets. We exploit the emotional knowledge inside those texts by using emojis and hashtags as weakly supevised label. Our system ranked Top 3 in SemEval 2018: Affect in Tweets a well-known competition in the NLP research community. blog: a50b7e93384f paper: Buzzwords: Natural Language Processing Sentiment Analysis Representation Learning Level: Intermediate: Target audiences with intermediate experience in python programming Requirements to Audiences: Nil Language: English Speaker: Ji Ho Park South Korea Speaker Bio: Ji Ho is from Korea but lived in HK for almost 6 years. He graduated from Hong Kong University of Science and Technology HKUST with a Master of PhilosophyMPhil. His research area is in natural language processing and machine learning especially on sentimentemotion analysis and automatic abusive language detection. Now he is currently working at Oyalabs a HK baby-tech startup as a machine learning engineer NLP. GitHub: github.comjihopark LinkedIn: WebsiteBlog: medium.comparkjiho,

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