CIDER: Context sensitive sentiment analysis for short-form text
Researchers commonly perform sentiment analysis on large collections of short texts like tweets, Reddit posts or newspaper headlines that are all focused on a specific topic, theme or event. Usually, general-purpose sentiment analysis methods are used. These perform well on average but miss the variation in meaning that happens across different contexts, for example, the word "active" has a very different intention and valence in the phrase "active lifestyle" versus "active volcano". This work presents a new approach, CIDER (Context Informed Dictionary and sEmantic Reasoner), which performs context-sensitive linguistic analysis, where the valence of sentiment-laden terms is inferred from the whole corpus before being used to score the individual texts. In this paper, we detail the CIDER algorithm and demonstrate that it outperforms state-of-the-art generalist unsupervised sentiment analysis techniques on a large collection of tweets about the weather. CIDER is also applicable to alternative (non-sentiment) linguistic scales. A case study on gender in the UK is presented, with the identification of highly gendered and sentiment-laden days. We have made our implementation of CIDER available as a Python package: https://pypi.org/project/ciderpolarity/.
Code (0)
등록된 구현이 없습니다.
Tasks
FormSentiment AnalysisSimilar Papers 제목 키워드 기반
Target-Sensitive Memory Networks for Aspect Sentiment Classification
Aspect sentiment classification (ASC) is a fundamental task in sentiment analysis. Given an aspect/target and a sentence, the task classifies the sentiment polarity expressed on the target in the sentence. Memory network…
Aspect-Based Sentiment Analysis (ABSA)ClassificationGeneral ClassificationSentence+2Context-Sensitive Lexicon Features for Neural Sentiment Analysis
Dependency Structure Augmented Contextual Scoping Framework for Multimodal Aspect-Based Sentiment Analysis
Multimodal Aspect-Based Sentiment Analysis (MABSA) seeks to extract fine-grained information from image-text pairs to identify aspect terms and determine their sentiment polarity. However, existing approaches often fall …
Aspect-Based Sentiment AnalysisDependency ParsingImage-text matchingSentiment Analysis+1Combination of Convolutional and Recurrent Neural Network for Sentiment Analysis of Short Texts
Sentiment analysis of short texts is challenging because of the limited contextual information they usually contain. In recent years, deep learning models such as convolutional neural networks (CNNs) and recurrent neural…
Information RetrievalSentiment AnalysisSpeech RecognitionWord EmbeddingsRecognizing Euphemisms and Dysphemisms Using Sentiment Analysis
This paper presents the first research aimed at recognizing euphemistic and dysphemistic phrases with natural language processing. Euphemisms soften references to topics that are sensitive, disagreeable, or taboo. Conver…
Sentiment Analysis