相关论文: Context-Aware Attention for Understanding Twitter …

Twitter has become one of the main sources of news for many people. As real-world events and emergencies unfold, Twitter is abuzz with hundreds of thousands of stories about the events. Some of these stories are harmless, while others could…

The success of online social platforms hinges on their ability to predict and understand user behavior at scale. Here, we present data suggesting that context-aware modeling approaches may offer a holistic yet lightweight and potentially…

Despite growing efforts to halt distasteful content on social media, multilingualism has added a new dimension to this problem. The scarcity of resources makes the challenge even greater when it comes to low-resource languages. This work…

Twitter, a popular social network, presents great opportunities for on-line machine learning research. However, previous research has focused almost entirely on learning from passively collected data. We study the problem of learning to…

Toxicity is endemic to online social networks including Twitter. It follows a Pareto like distribution where most of the toxicity is generated by a very small number of profiles and as such, analyzing and characterizing these toxic profiles…

As of today, abuse is a pressing issue to participants and administrators of Online Social Networks (OSN). Abuse in Twitter can spawn from arguments generated for influencing outcomes of a political election, the use of bots to…

During the onset of a disaster event, filtering relevant information from the social web data is challenging due to its sparse availability and practical limitations in labeling datasets of an ongoing crisis. In this paper, we hypothesize…

Harmful speech has various forms and it has been plaguing the social media in different ways. If we need to crackdown different degrees of hate speech and abusive behavior amongst it, the classification needs to be based on complex…

The increasing misuse of social media has become a concern; however, technological solutions are being developed to moderate its content effectively. This paper focuses on detecting abusive texts targeting women on social media platforms.…

Social media have been deliberately used for malicious purposes, including political manipulation and disinformation. Most research focuses on high-resource languages. However, malicious actors share content across countries and languages,…

Hate speech has grown significantly on social media, causing serious consequences for victims of all demographics. Despite much attention being paid to characterize and detect discriminatory speech, most work has focused on explicit or…

People post information about different topics which are in their active vocabulary over social media platforms (like Twitter, Facebook, PInterest and Google+). They follow each other and it is more likely that the person who posts…

In this paper, we address the problem of detecting expressions of moral values in tweets using content analysis. This is a particularly challenging problem because moral values are often only implicitly signaled in language, and tweets…

Offensive language is pervasive in social media. Individuals frequently take advantage of the perceived anonymity of computer-mediated communication, using this to engage in behavior that many of them would not consider in real life. The…

In the recent years, we have witnessed the rapid adoption of social media platforms, such as Twitter, Facebook and YouTube, and their use as part of the everyday life of billions of people worldwide. Given the habit of people to use these…

Language use changes over time, and this impacts the effectiveness of NLP systems. This phenomenon is even more prevalent in social media data during crisis events where meaning and frequency of word usage may change over the course of…

Intent detection is a crucial component of modern conversational systems, since accurately identifying user intent at the beginning of a conversation is essential for generating effective responses. Recent efforts have focused on studying…

The detection of offensive, hateful and profane language has become a critical challenge since many users in social networks are exposed to cyberbullying activities on a daily basis. In this paper, we present an analysis of combining…

Thanks to platforms such as Twitter and Facebook, people can know facts and events that otherwise would have been silenced. However, social media significantly contribute also to fast spreading biased and false news while targeting specific…

Spoken language understanding (SLU) is an essential component in conversational systems. Most SLU component treats each utterance independently, and then the following components aggregate the multi-turn information in the separate phases.…