Online harassment. (2018)
- Record Type:
- Book
- Title:
- Online harassment. (2018)
- Main Title:
- Online harassment
- Further Information:
- Note: Jennifer Golbeck, editor.
- Editors:
- Golbeck, Jennifer
- Contents:
- Intro; Contents; Contributors; 1 Online Harassment: A Research Challenge for HCI; Detection; 2 Weak Supervision and Machine Learning for Online Harassment Detection; 2.1 Introduction; 2.2 Related Work; 2.2.1 Machine Learning for Detection of Online Harassment and Related Phenomena; 2.2.2 Weakly Supervised Machine Learning; 2.3 Participant-Vocabulary Consistency; 2.3.1 Model Details; 2.3.2 Learning the Parameters; 2.4 Experiments; 2.4.1 Data Processing; 2.4.2 Baselines; 2.4.3 Human Annotation Comparisons; 2.4.4 Qualitative Analysis; 2.5 Discussion, Extensions, and Open Problems 2.5.1 Deep Learning2.5.2 Fairness; 2.5.3 Weak Supervision Interface; 2.5.4 Automated Interventions; References; 3 Bridging the Gaps: Multi Task Learning for Domain Transfer of Hate Speech Detection; 3.1 Introduction; 3.1.1 Hate Speech Detection; 3.1.2 Multi-task Learning; 3.1.3 Utility of Multi-task Learning for Hate Speech Detection; 3.2 Data; 3.2.1 Understandings of ``Hate Speech''; 3.2.2 Commonalities and Differences; 3.3 Model; 3.3.1 Baseline Model Definition; 3.3.2 Multi-task Model Definition; 3.3.3 Training; 3.3.4 Features; 3.3.5 Pre-processing; 3.4 Experiments; 3.4.1 Baseline Models 3.4.2 Composite Data Models3.4.3 Multi-task Learning Models; 3.4.4 Dataset Statistics; 3.4.5 Evaluation Metrics; 3.5 Experimental Results; 3.5.1 Single-Task Baseline Models; 3.5.2 Composite Dataset Models; 3.5.3 Multi-task Learning Models; 3.5.4 Critiques of Datasets; 3.6 Related Work; 3.6.1 Abusive Language; 3.6.2Intro; Contents; Contributors; 1 Online Harassment: A Research Challenge for HCI; Detection; 2 Weak Supervision and Machine Learning for Online Harassment Detection; 2.1 Introduction; 2.2 Related Work; 2.2.1 Machine Learning for Detection of Online Harassment and Related Phenomena; 2.2.2 Weakly Supervised Machine Learning; 2.3 Participant-Vocabulary Consistency; 2.3.1 Model Details; 2.3.2 Learning the Parameters; 2.4 Experiments; 2.4.1 Data Processing; 2.4.2 Baselines; 2.4.3 Human Annotation Comparisons; 2.4.4 Qualitative Analysis; 2.5 Discussion, Extensions, and Open Problems 2.5.1 Deep Learning2.5.2 Fairness; 2.5.3 Weak Supervision Interface; 2.5.4 Automated Interventions; References; 3 Bridging the Gaps: Multi Task Learning for Domain Transfer of Hate Speech Detection; 3.1 Introduction; 3.1.1 Hate Speech Detection; 3.1.2 Multi-task Learning; 3.1.3 Utility of Multi-task Learning for Hate Speech Detection; 3.2 Data; 3.2.1 Understandings of ``Hate Speech''; 3.2.2 Commonalities and Differences; 3.3 Model; 3.3.1 Baseline Model Definition; 3.3.2 Multi-task Model Definition; 3.3.3 Training; 3.3.4 Features; 3.3.5 Pre-processing; 3.4 Experiments; 3.4.1 Baseline Models 3.4.2 Composite Data Models3.4.3 Multi-task Learning Models; 3.4.4 Dataset Statistics; 3.4.5 Evaluation Metrics; 3.5 Experimental Results; 3.5.1 Single-Task Baseline Models; 3.5.2 Composite Dataset Models; 3.5.3 Multi-task Learning Models; 3.5.4 Critiques of Datasets; 3.6 Related Work; 3.6.1 Abusive Language; 3.6.2 Multi-task Learning; 3.7 Conclusion; 3.8 Future Work; References; 4 A Network Analysis of the GamerGate Movement; 4.1 The Network; 4.2 #OpSkynet; 4.3 #NotYourShield; 4.4 #SJWs; 4.5 #GamerGate; 4.6 Signal Boosters (Edge Class 0); 4.6.1 Structural Analysis; 4.6.2 Content Analysis 4.6.3 Conclusions: Edge Class 04.7 Flag Bearers (Edge Class 1); 4.7.1 Structural Analysis; 4.7.2 Content Analysis; 4.7.3 Conclusions: Edge Class 1; 4.8 Activists and Advocates (Edge Class 2); 4.8.1 Structural Analysis; 4.8.2 Content Analysis; 4.8.3 R/TheOpenHouse (@Rsolgtp); 4.8.4 I'm a Consumer (@Imaconsumer); 4.8.5 Ethan2478 (@GuidesGame); 4.8.6 A Man in Camouflage (@the_Sgt_Maj), Lalafell Warrior X (@Fuzzytoad), and Frankie Sweets @TheSweetsTweet; 4.8.7 Conclusions; 4.9 Generals (Edge Class 4); 4.9.1 Structural Analysis; 4.9.2 Content Analysis; 4.9.3 Conclusions: Edge Class 4 4.10 Soldiers (Edge Class 5)4.10.1 Structural Analysis; 4.10.2 Content Analysis; 4.11 The Spectrum (Edge Class 6); 4.11.1 Structural Analysis; 4.11.2 Content Analysis; 4.11.3 Conclusions; 4.12 Overall Conclusions; 4.12.1 No Single Narrative; 4.12.2 Post-feminist Leadership; 4.12.3 Reports of My Death…; 4.12.4 Directions for Future Study; References; 5 Automation and Harassment Detection; 5.1 Introduction; 5.2 First Attempt: Just Code; 5.3 A Little Help from Statistics; 5.4 A First Attempt with Machine Learning; 5.5 Improving Our Model; 5.6 Domain Matters: A Tail of Two Distributions … (more)
- Publisher Details:
- Cham, Switzerland : Springer
- Publication Date:
- 2018
- Extent:
- 1 online resource
- Subjects:
- 302.343
Computer science
Cyberbullying
Harassment
Internet -- Social aspects
PSYCHOLOGY / Social Psychology
Cyberbullying
Harassment
Internet -- Social aspects
Language Arts & Disciplines -- Linguistics -- General
Social Science -- Media Studies
Computational linguistics
Media studies
Computational linguistics
Social media
Computers -- User Interfaces
User interface design & usability
Electronic books - Languages:
- English
- ISBNs:
- 9783319785837
3319785834 - Related ISBNs:
- 9783319785820
3319785826 - Notes:
- Note: Online resource; title from PDF title page (EBSCO, viewed July 25, 2018).
- Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.358705
- Ingest File:
- 01_320.xml