Textmining at EmoInt-2017: A Deep Learning Approach to Sentiment Intensity Scoring of English Tweets

2017-09-01 · WS 2017 9 · Hardik Meisheri, Rupsa Saha, Priyanka Sinha, Lipika Dey

This paper describes our approach to the Emotion Intensity shared task. A parallel architecture of Convolutional Neural Network (CNN) and Long short term memory networks (LSTM) alongwith two sets of features are extracted which aid the network in judging emotion intensity. Experiments on different models and various features sets are described and analysis on results has also been presented.

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Tasks

Sentiment AnalysisWord Embeddings

UWat-Emote at EmoInt-2017: Emotion Intensity Detection using Affect Clues, Sentiment Polarity and Word Embeddings

2017-09-01 · WS 2017 9 · Vineet John, Olga Vechtomova

This paper describes the UWaterloo affect prediction system developed for EmoInt-2017. We delve into our feature selection approach for affect intensity, affect presence, sentiment intensity and sentiment presence lexica…

Emotion Classification Ensemble Learning feature selection regression+1

YZU-NLP at EmoInt-2017: Determining Emotion Intensity Using a Bi-directional LSTM-CNN Model

2017-09-01 · WS 2017 9 · Yuanye He, Liang-Chih Yu, K. Robert Lai, Weiyi Liu

The EmoInt-2017 task aims to determine a continuous numerical value representing the intensity to which an emotion is expressed in a tweet. Compared to classification tasks that identify 1 among n emotions for a tweet, t…

General Classification Sentiment Analysis Word Embeddings

Tecnolengua Lingmotif at EmoInt-2017: A lexicon-based approach

2017-09-01 · WS 2017 9 · Antonio Moreno-Ortiz

In this paper we describe Tecnolengua Group{'}s participation in the shared task on emotion intensity at WASSA 2017. We used the Lingmotif tool and a new, complementary tool, Lingmotif Learn, which we developed for this …

Sentiment Analysis

PLN-PUCRS at EmoInt-2017: Psycholinguistic features for emotion intensity prediction in tweets

2017-09-01 · WS 2017 9 · Henrique Santos, Renata Vieira

Linguistic Inquiry and Word Count (LIWC) is a rich dictionary that map words into several psychological categories such as Affective, Social, Cognitive, Perceptual and Biological processes. In this work, we have used LIW…

regression Sentiment Analysis

YNU-HPCC at EmoInt-2017: Using a CNN-LSTM Model for Sentiment Intensity Prediction

2017-09-01 · WS 2017 9 · You Zhang, Hang Yuan, Jin Wang, Xue-jie Zhang

In this paper, we present a system that uses a convolutional neural network with long short-term memory (CNN-LSTM) model to complete the task. The CNN-LSTM model has two combined parts: CNN extracts local n-gram features…