相关论文: How is Your Mood When Writing Sexist tweets? Detec…

Large Language Models (LLMs) have demonstrated impressive performance across various tasks, including sentiment analysis. However, data quality--particularly when sourced from social media--can significantly impact their accuracy. This…

Anticipating audience reaction towards a certain piece of text is integral to several facets of society ranging from politics, research, and commercial industries. Sentiment analysis (SA) is a useful natural language processing (NLP)…

The phenomenal growth on the internet has helped in empowering individual's expressions, but the misuse of freedom of expression has also led to the increase of various cyber crimes and anti-social activities. Hate speech is one such issue…

Emotion classification in text is a challenging task due to the processes involved when interpreting a textual description of a potential emotion stimulus. In addition, the set of emotion categories is highly domain-specific. For instance,…

Sentiment analysis (also known as opinion mining) refers to the use of natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials. Mining opinions expressed in…

We present the findings of our participation in the SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS) task, a shared task on offensive language (sexism) detection on English Gab and Reddit dataset. We investigated the…

Tweets pertaining to a single event, such as a national election, can number in the hundreds of millions. Automatically analyzing them is beneficial in many downstream natural language applications such as question answering and…

The massive popularity of online social media provides a unique opportunity for researchers to study the linguistic characteristics and patterns of user's interactions. In this paper, we provide an in-depth characterization of language…

Sentiment analysis on software engineering (SE) texts has been widely used in the SE research, such as evaluating app reviews or analyzing developers sentiments in commit messages. To better support the use of automated sentiment analysis…

In this effort we fine tuned different models based on BERT to detect the gender polarity of twitter accounts. We specially focused on analyzing the effect of using emojis and emoticons in performance of our model in classifying task. We…

Stating your gender pronouns, along with your name, is becoming the new norm of self-introductions at school, at the workplace, and online. The increasing prevalence and awareness of nonconforming gender identities put discussions of…

Stance classification aims to identify, for a particular issue under discussion, whether the speaker or author of a conversational turn has Pro (Favor) or Con (Against) stance on the issue. Detecting stance in tweets is a new task proposed…

People use the world wide web heavily to share their experience with entities such as products, services, or travel destinations. Texts that provide online feedback in the form of reviews and comments are essential to make consumer…

Sentiment analysis or opinion mining has become an open research domain after proliferation of Internet and Web 2.0 social media. People express their attitudes and opinions on social media including blogs, discussion forums, tweets, etc.…

We consider the distinction between intended and perceived sarcasm in the context of textual sarcasm detection. The former occurs when an utterance is sarcastic from the perspective of its author, while the latter occurs when the utterance…

Social media has become an everyday means of interaction and information sharing on the Internet. However, posts on social networks are often aggressive and toxic, especially when the topic is controversial or politically charged.…

The Gender Identification (GI) problem is concerned with determining the gender of the author from a given text. It has numerous applications in different fields like forensics, literature, security, marketing, trade, etc. Due to its…

Sentiment analysis of social media data is an emerging field with vast applications in various domains. In this study, we developed a sentiment analysis model to analyze social media sentiment, especially tweets, during global conflicting…

This study investigates gender-based differences in online communication patterns of academics, focusing on how male and female academics represent themselves and how users interact with them on the social media platform X (formerly…

In this era of digitization, knowing the user's sociolect aspects have become essential features to build the user specific recommendation systems. These sociolect aspects could be found by mining the user's language sharing in the form of…