Identifying Expressions of Emotion in Text

By Saima Aman, Stan Szpakowicz. International Conference on Text, Speech and Dialogue, 2007

511 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/6ec802c9a6032391c68c75bf5c7b3d0057c17e31

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In Artificial Intelligence

Citations in the corpus

Using Hashtags to Capture Fine Emotion Categories from Tweets (2015, background): “Other datasets with sentence-level annotations of emotions include about 4000 sentences from blogs, compiled by Aman and Szpakowicz (2007); 1000 sentences from stories on topics such as education and health, compiled by Neviarouskaya et al. (2009); and about 4000 sentences from fairy tales,…”
EmoNet: Fine-Grained Emotion Detection with Gated Recurrent Neural Networks (2017, background): “Similarly, (Aman and Szpakowicz, 2007) describe an emotion annotation task of identifying emotion category, emotion intensity and the words/phrases that indicate emotion in blog post data of 4,090 sentences and a system exploiting the data.”
A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks (2016, methodology): “As a dataset for extracting emotion-related features, we use the corpus developed by (Aman and Szpakowicz, 2007).”
Sentiment Analysis: Detecting Valence, Emotions, and Other Affectual States from Text (2016, background): “Keywords: sentiment analysis, emotions, artificial intelligence, machine learning, natural language processing (NLP), social media, emotion lexicons, fairness in NLP”
Dealing with Disagreements: Looking Beyond the Majority Vote in Subjective Annotations (2021, background): “Detecting emotions from language has been a significant area of research in NLP for the past two decades (Liscombe et al., 2003; Aman and Szpakowicz, 2007; Desmet and Hoste, 2013; Hirschberg and Manning, 2015; Poria et al., 2019).”
Challenges in Sentiment Analysis (2017, unknown): “…arousal and a relatively small amount of work on detecting emotions such as anger, frustration, sadness, and optimism (Strapparava & Mihalcea, 2007; Aman & Szpakowicz, 2007; Tokuhisa, Inui, & Matsumoto, 2008; Neviarouskaya, Prendinger, & Ishizuka, 2009; Bellegarda, 2010; Mohammad, 2012;…”
#Emotional Tweets (2012, methodology): “Other datasets with sentence-level annotations of emotions include about 4000 sentences from blogs, compiled by Aman and Szpakowicz (2007); 1000 sentences from stories on topics such as education and health, compiled by Neviarouskaya et al. (2009); and about 4000 sentences from fairy tales,…”
CROWDSOURCING A WORD–EMOTION ASSOCIATION LEXICON (2013, background): “…the tendency of terms to co-occur with seed words whose emotions are known (Read, 2004), some use hand-coded rules (Neviarouskaya et al. , 2009, 2010), and some use machine learning and a number of emotion features, including emotion denoting words (Alm et al. , 2005; Aman and Szpakowicz, 2007).”