Твиттер жазбалары

Microblogging networks serve as vehicles for reaching and influencing users. Predicting whether a message will elicit a user response opens the possibility of maximizing the viral- ity, reach and effectiveness …...

We propose a method for using discourse rela- tions for polarity detection of tweets. We have focused on unstructured and noisy text like tweets on which linguistic tools like parsers …...

This paper presents our system, TJP, which participated in SemEval 2013 Task 2 part A: Contextual Polarity Disambiguation. The goal of this task is to predict whether marked con- texts …...

In this paper, we describe the development and performance of the supervised system UMCC_DLSI-(SA). This system uses corpora where phrases are annotated as Positive, Negative, Objective, and Neutral, to achieve …...

Story highlights form a succinct single-document summary consisting of 3-4 highlight sentences that reflect the gist of a news article. Automatically producing news highlights is very challeng- ing. We propose …...

This report summarizes the objectives and evaluation of the SemEval 2015 task on the sentiment analysis of figurative language on Twitter (Task 11). This is the first sentiment analysis task …...

AbstractCyberbullying statistics are shocking, the number of affected young people is increasing dramatically with the affordability of mobile technology devices combined with a growing number of social networks. This paper …...

AbstractThe increasing streams of information pose challenges to both humans and machines. On the one hand, humans need to identify relevant information and consume only the information that lies at …...

Event extraction from texts aims to de- tect structured information such as what has happened, to whom, where and when. Event extraction and visualization are typ- ically considered as two …...

Part-of-speech (POS) taggers trained on newswire perform much worse on domains such as subtitles, lyrics, or tweets. In addition, these domains are also heterogeneous, e.g., with respect to registers and …...

AbstractThe paper contains a description of OPFI: Opinion Finder for the Polish Language, a freely available tool for opinion target extraction. The goal of the tool is opinion finding: a …...

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 …...

AbstractRecently emerged intelligent assistants on smartphones and home electronics (e.g., Siri and Alexa) can be seen as novel hybrids of domain-specific task-oriented spoken dialogue systems and open-domain non-task-oriented ones. To …...

AbstractIn this work, we study the problem of part-of-speech tagging for Tweets. In contrast to newswire articles, Tweets are usually informal and contain numerous out-of-vocabulary words. Moreover, there is a …...

Emoji are pictographs commonly used in microblogs as emotion markers, but they can also represent a much wider range of concepts. Additionally, they may occur in different positions within a …...

AbstractThis paper describes the NeuroSent system that participated in SemEval 2018 Task 3. Our system takes a supervised approach that builds on neural networks and word embeddings. Word embeddings were …...

AbstractThe advent of micro-blogging sites has paved the way for researchers to collect and analyze huge volumes of data in recent years. Twitter, being one of the leading social networking …...

AbstractThe massive growth of user-generated web content through blogs, online forums and most notably, social media networks, led to a large spreading of hatred or abusive messages which have to …...

AbstractLegislator preferences are typically represented as measures of general ideology estimated from roll call votes on legislation, potentially masking important nuances in legislators’ political attitudes. In this paper we introduce …...

AbstractTweets are specific text data when compared to general text. Although sentiment analysis over tweets has become very popular in the last decade for English, it is still difficult to …...

AbstractTwitter has become a major platform for users to express their opinions on any topic and engage in debates. User debates and interactions usually lead to massive content regarding a …...

AbstractWe introduce the well-established social scientific concept of social solidarity and its contestation, anti-solidarity, as a new problem setting to supervised machine learning in NLP to assess how European solidarity …...

AbstractSemantic sentence embeddings are usually supervisedly built minimizing distances between pairs of embeddings of sentences labelled as semantically similar by annotators. Since big labelled datasets are rare, in particular for …...

AbstractIt is challenging to design profitable and practical trading strategies, as stock price movements are highly stochastic, and the market is heavily influenced by chaotic data across sources like news …...

AbstractThe rapid spread of information over social media influences quantitative trading and investments. The growing popularity of speculative trading of highly volatile assets such as cryptocurrencies and meme stocks presents …...

AbstractThe paper describes our submission to SemEval-2022 Task 6 on sarcasm detection and its five subtasks for English and Arabic. Sarcasm conveys a meaning which contradicts the literal meaning, and …...

We present the results of a project perform- ing sentiment analysis on tweets from Ger- man politicians and party accounts for the 2021 German federal election. We collected over 58,000 …...

In this paper, we propose a method of min- ing tweets that represent reviews on celebrities by the machine reading comprehension model based on BERT. The purpose of this paper …...

AbstractMoral rhetoric influences our judgement. Although social scientists recognize moral expression as domain specific, there are no systematic methods for analyzing whether a text classifier learns the domain-specific expression of …...