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NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets
TLDR
In this paper, we describe how we created two state-of-the-art SVM classifiers, one to detect the sentiment of messages such as tweets and SMS (message-level task). Expand
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CROWDSOURCING A WORD–EMOTION ASSOCIATION LEXICON
TLDR
In this paper, we show how the combined strength and wisdom of the crowds can be used to generate a large, high‐quality, word–emotion and word–polarity association lexicon quickly and inexpensively. Expand
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SemEval-2016 Task 6: Detecting Stance in Tweets
TLDR
We present a shared task on detecting stance from tweets: given a tweet and a target entity (person, organization, etc.), automatic natural language systems must determine whether the tweeter is in favor of the given target, against, or neutral towards a proposition or target. Expand
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Sentiment Analysis of Short Informal Texts
TLDR
We describe a state-of-the-art sentiment analysis system that detects (a) the sentiment of short informal textual messages such as tweets and SMS (message-level task). Expand
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SemEval-2018 Task 1: Affect in Tweets
TLDR
We present the SemEval-2018 Task 1: Affect in Tweets, which includes an array of subtasks on inferring the affectual state of a person from their tweet. Expand
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NRC-Canada-2014: Detecting Aspects and Sentiment in Customer Reviews
TLDR
We present supervised machine-learning approaches to detect aspect terms and aspect categories and to detect sentiment expressed towards aspect terms in customer reviews. Expand
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Stance and Sentiment in Tweets
TLDR
We propose a simple stance detection system that outperforms submissions from all 19 teams in a SemEval-2016 shared task competition. Expand
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#Emotional Tweets
TLDR
In this paper, we show how we created a large dataset of more than 20,000 emotion-word hashtags from Twitter posts using emotion hashtags. Expand
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Emotions Evoked by Common Words and Phrases: Using Mechanical Turk to Create an Emotion Lexicon
TLDR
In this paper, we show how we create a high-quality, moderate-sized emotion lexicon using Mechanical Turk. Expand
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SemEval-2015 Task 10: Sentiment Analysis in Twitter
TLDR
In this paper, we describe the 2015 iteration of the SemEval shared task on Sentiment Analysis in Twitter. Expand
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