Threat detection in online discussions

نویسندگان

  • Aksel Wester
  • Lilja Øvrelid
  • Erik Velldal
  • Hugo Hammer
چکیده

This paper investigates the effect of various types of linguistic features (lexical, syntactic and semantic) for training classifiers to detect threats of violence in a corpus of YouTube comments. Our results show that combinations of lexical features outperform the use of more complex syntactic and semantic features for this task.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Effects of Receiving Corrective Feedback through Online Chats and Class Discussions on Iranian EFL Learners' Writing Quality

Giving corrective feedback (CF) is an essential part of the teaching and learning process, and the way it should beneficially be done has been the focus of attention for numerous researchers especially when traditional ways of CF provision are not possible, particularly in rare situations such as outbreaks of diseases. This study investigated how different ways of giving feedback; namely, throu...

متن کامل

Feature-based Malicious URL and Attack Type Detection Using Multi-class Classification

Nowadays, malicious URLs are the common threat to the businesses, social networks, net-banking etc. Existing approaches have focused on binary detection i.e. either the URL is malicious or benign. Very few literature is found which focused on the detection of malicious URLs and their attack types. Hence, it becomes necessary to know the attack type and adopt an effective countermeasure. This pa...

متن کامل

A case-based approach for teaching professionalism to residents with online discussions

Introduction: Programs must demonstrate that their residentsare taught and assessed in professionalism. Most programsstruggle with finding viable ways to teach and assess this criticalcompetency. UTHSCSA Family and Community MedicineResidency developed an innovative option for interactive learningand assessment of residents in this competency which would betransferrable to other programs and sp...

متن کامل

Online multiple people tracking-by-detection in crowded scenes

Multiple people detection and tracking is a challenging task in real-world crowded scenes. In this paper, we have presented an online multiple people tracking-by-detection approach with a single camera. We have detected objects with deformable part models and a visual background extractor. In the tracking phase we have used a combination of support vector machine (SVM) person-specific classifie...

متن کامل

BotOnus: an online unsupervised method for Botnet detection

Botnets are recognized as one of the most dangerous threats to the Internet infrastructure. They are used for malicious activities such as launching distributed denial of service attacks, sending spam, and leaking personal information. Existing botnet detection methods produce a number of good ideas, but they are far from complete yet, since most of them cannot detect botnets in an early stage ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016