Определение настроения

Supervised classification needs large amounts of annotated training data that is expensive to create. Two approaches that reduce the cost of annotation are active learning and crowd- sourcing. However, these …...

AbstractThere have been increasing interests in recent years in analyzing tweet messages relevant to political events so as to understand public opinions towards certain political issues. We analyzed tweet messages …...

We present a supervised sentiment detection system that classifies the polarity of subjec- tive phrases as positive, negative, or neutral. It is tailored towards online genres, specifically Twitter, through the …...

This paper describes an expression-level senti- ment detection system that participated in the subtask A of SemEval-2013 Task 2: Senti- ment Analysis in Twitter. Our system uses a supervised approach …...

In this paper, we describe how we created two state-of-the-art SVM classifiers, one to de- tect the sentiment of messages such as tweets and SMS (message-level task) and one to …...

Semantic word spaces have been very use- ful but cannot express the meaning of longer phrases in a principled way. Further progress towards understanding compositionality in tasks such as sentiment …...

This paper addresses implicit opinions expressed via inference over explicit sentiments and events that positively/negatively affect entities (goodFor/badFor, gfbf events). We incorporate the inferences developed by implicature rules into an …...

AbstractIn this paper, we analyze the quality of several commercial tools for sentiment detection. All tools are tested on nearly 30,000 short texts from various sources, such as tweets, news, …...

Reviews depict sentiments of customers towards various aspects of a product or service. Some of these aspects can be grouped into coarser aspect categories. SemEval-2014 had a shared task (Task …...

This paper describe a weakly supervised so- lution for detecting stance in tweets, submit- ted to the SemEval 2016 Stance Task. Our approach is based on the premise that stance …...

Linguistic research on multilingual societies has indicated that there is usually a preferred language for expression of emotion and sen- timent (Dewaele, 2010). Paucity of data has limited such studies …...

AbstractEmojis are widely used on social media andunderstanding their meaning is important forboth practical purposes (e.g. opinion mining,sentiment detection) and theoretical purposes(e.g. how different L1 speakers use them, dothey have …...

AbstractMultilingual writers and speakers often alternate between two languages in a single discourse. This practice is called “code-switching”. Existing sentiment detection methods are usually trained on sentiment-labeled monolingual text. Manually …...

AbstractIn sentiment detection, the natural language processing community has focused on determining holders, facets, and valences, but has paid little attention to the reasons for sentiment decisions. Our work considers …...

AbstractWe present a neural network based approach of transfer learning for offensive language detection. For our system, we compare two types of knowledge transfer: supervised and unsupervised pre-training. Supervised pre-training …...

AbstractIt is fairly common to use code-mixing on a social media platform to express opinions and emotions in multilingual societies. The purpose of this task is to detect the sentiment …...

AbstractAs multimodal learning finds applications in a wide variety of high-stakes societal tasks, investigating their robustness becomes important. Existing work has focused on understanding the robustness of vision-and-language models to …...