Combining textual features to detect cyberbullying in social media posts
نویسندگان
چکیده
منابع مشابه
Assessing the quality of textual features in social media
Social media is increasingly becoming a significant fraction of the content retrieved daily by Web users. However, the potential lack of quality of user generated content poses a challenge to information retrieval services, which rely mostly on textual features generated by users (particularly tags) commonly associated with the multimedia objects. This paper presents what, to the best of our kn...
متن کاملSentiment Informed Cyberbullying Detection in Social Media
Cyberbullying is a phenomenon which negatively affects the individuals, the victims suffer from various mental issues, ranging from depression, loneliness, anxiety to low self-esteem. In parallel with the pervasive use of social media, cyberbullying is becoming more and more prevalent. Traditional mechanisms to fight against cyberbullying include the use of standards and guidelines, human moder...
متن کاملSpoiler Alert: Machine Learning Approaches to Detect Social Media Posts with Revelatory Information
Spoilers—critical plot information about works of fiction that “spoil” a viewer’s enjoyment—have prompted elaborate conventions on social media to allow readers to insulate themselves from spoilers. However, these solutions depend on the conscientiousness and rigor of Internet posters and are thus an imperfect system. We create an automatic alternative that could alert users when a piece of tex...
متن کاملGeolocating social media posts for emergency mapping
edemowill illustrate the features of awebGIS interface to support the rapid mapping activities aer a natural disaster, with the goal of providing additional information from social media to the mapping operators. is demo shows the rst results of the E2mC H2020 European project, where the goal is to extract precisely located information from available social media sources, providing accurate...
متن کاملImproving geolocation of social media posts
Pervasive social systems often take advantage of geographical information to provide real-time information to users based on their location. However, due to privacy concerns, many social media users do not share their exact geographical coordinates. In this paper, we describe our technique that predicts locations of posts that are not associated with explicit coordinates, a process called geolo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2020
ISSN: 1877-0509
DOI: 10.1016/j.procs.2020.08.063