"With 1 follower I must be AWESOME :P". Exploring the role of irony markers in irony recognition
Conversations in social media often contain the use of irony or sarcasm, when the users say the opposite of what they really mean. Irony markers are the meta-communicative clues that inform the reader that an utterance is ironic. We propose a thorough analysis of theoretically grounded irony markers in two social media platforms: $Twitter$ and $Reddit$. Classification and frequency analysis show that for $Twitter$, typographic markers such as emoticons and emojis are the most discriminative markers to recognize ironic utterances, while for $Reddit$ the morphological markers (e.g., interjections, tag questions) are the most discriminative.
Code (0)
등록된 구현이 없습니다.
Tasks
General ClassificationTAGSimilar Papers 제목 키워드 기반
ValenTO at SemEval-2018 Task 3: Exploring the Role of Affective Content for Detecting Irony in English Tweets
In this paper we describe the system used by the ValenTO team in the shared task on Irony Detection in English Tweets at SemEval 2018. The system takes as starting point emotIDM, an irony detection model that explores th…
Sentiment AnalysisExploring the Realization of Irony in Twitter Data
Handling figurative language like irony is currently a challenging task in natural language processing. Since irony is commonly used in user-generated content, its presence can significantly undermine accurate analysis o…
Sentiment AnalysisMonday mornings are my fave :) \#not Exploring the Automatic Recognition of Irony in English tweets
Recognising and understanding irony is crucial for the improvement natural language processing tasks including sentiment analysis. In this study, we describe the construction of an English Twitter corpus and its annotati…
Opinion MiningSentiment AnalysisExploring the Impact of Pragmatic Phenomena on Irony Detection in Tweets: A Multilingual Corpus Study
This paper provides a linguistic and pragmatic analysis of the phenomenon of irony in order to represent how Twitter{'}s users exploit irony devices within their communication strategies for generating textual contents. …
Sentiment AnalysisSSN MLRG1 at SemEval-2018 Task 3: Irony Detection in English Tweets Using MultiLayer Perceptron
Sentiment analysis plays an important role in E-commerce. Identifying ironic and sarcastic content in text plays a vital role in inferring the actual intention of the user, and is necessary to increase the accuracy of se…
feature selectionOpinion MiningSarcasm DetectionSentiment Analysis