12 papers · ranked by Valyu relevance
Vedant Sandeep Joshi, Sivanagaraja Tatinati, Yübo Wang
On current e-learning platforms, live classes are an important tool that provides students with an opportunity to get more involved while learning new concepts. In such classes, the element of interaction with teachers and fellow peers helps in removing learning silos and gives each student a chance to experience some…
Salim Sazzed, Kathiravan Srinivasan
Bengali is a low-resource language that lacks tools and resources for various natural language processing (NLP) tasks, such as sentiment analysis or profanity identification. In Bengali, only the translated versions of English sentiment lexicons are available. Moreover, no dictionary exists for detecting profanity in…
Vikram Gupta, Rini A Sharon, Ramit Sawhney, Debdoot Mukherjee
Abusive content detection in spoken text can be addressed by performing Automatic Speech Recognition (ASR) and leveraging advancements in natural language processing. However, ASR models introduce latency and often perform suboptimally for profane words as they are underrepresented in training corpora and not spoken…
Abdulaziz Saleh Ba Wazir, Hezerul Abdul Karim, Mohd Haris Lye Abdullah, Nouar AlDahoul + 5 more
'Mohd Haris Lye Abdullah' 'Nouar AlDahoul' 'Sarina Mansor' 'Mohammad Faizal Ahmad Fauzi' 'John See' 'Ahmad Syazwan Naim' 'Wookey Lee'] Given the excessive foul language identified in audio and video files and the detrimental consequences to an individual’s character and behaviour, content censorship is crucial to…
Vanessa Hahn, Dana Ruiter, Thomas Kleinbauer, Dietrich Klakow
Hate speech and profanity detection suffer from data sparsity, especially for languages other than English, due to the subjective nature of the tasks and the resulting annotation incompatibility of existing corpora. In this study, we identify profane subspaces in word and sentence representations and explore their…
Noman Ashraf, Arkaitz Zubiaga, Alexander Gelbukh, Sebastian Ventura
Nowadays, social media experience an increase in hostility, which leads to many people suffering from online abusive behavior and harassment. We introduce a new publicly available annotated dataset for abusive language detection in short texts. The dataset includes comments from YouTube, along with contextual…
Shervin Malmasi, Marcos Zampieri
In this study we approach the problem of distinguishing general profanity from hate speech in social media, something which has not been widely considered. Using a new dataset annotated specifically for this task, we employ supervised classification along with a set of features that includes n-grams, skip-grams and…
Wenjie Yin, Arkaitz Zubiaga
While social media offers freedom of self-expression, abusive language carry significant negative social impact. Driven by the importance of the issue, research in the automated detection of abusive language has witnessed growth and improvement. However, these detection models display a reliance on strongly indicative…
Shervin Malmasi, Marcos Zampieri
In this paper we examine methods to detect hate speech in social media, while distinguishing this from general profanity. We aim to establish lexical baselines for this task by applying supervised classification methods using a recently released dataset annotated for this purpose. As features, our system uses character…
Shiri Lev-Ari, Ryan McKay
Why do swear words sound the way they do? Swear words are often thought to have sounds that render them especially fit for purpose, facilitating the expression of emotion and attitude. To date, however, there has been no systematic cross-linguistic investigation of phonetic patterns in profanity. In an initial, pilot…
Waqar Husain, Samia Wasif, Insha Fatima
Background Swearing is an increasing trend among men and women worldwide. Earlier studies on the positive aspects of profanity mostly relate to pain management and the release of negative emotions. The uniqueness of the current study is its analysis for a possible constructive role of profanity in stress, anxiety, and…
Wenjie Yin, Arkaitz Zubiaga, Yilun Shang
Hate speech is one type of harmful online content which directly attacks or promotes hate towards a group or an individual member based on their actual or perceived aspects of identity, such as ethnicity, religion, and sexual orientation. With online hate speech on the rise, its automatic detection as a natural…