Atoum, 2023 - Google Patents
Detecting cyberbullying from tweets through machine learning techniques with sentiment analysisAtoum, 2023
- Document ID
- 4084360801336664766
- Author
- Atoum J
- Publication year
- Publication venue
- Future of Information and Communication Conference
External Links
Snippet
Technology advancement has resulted in a serious problem called cyberbullying. Bullying someone online, typically by sending ominous or threatening messages, is known as cyberbullying. On social networking sites, Twitter in particular is evolving into a venue for this …
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/3071—Clustering or classification including class or cluster creation or modification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30705—Clustering or classification
- G06F17/30707—Clustering or classification into predefined classes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F17/30634—Querying
- G06F17/30657—Query processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30861—Retrieval from the Internet, e.g. browsers
- G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
- G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/20—Handling natural language data
- G06F17/27—Automatic analysis, e.g. parsing
- G06F17/2765—Recognition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/04—Inference methods or devices
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce, e.g. shopping or e-commerce
- G06Q30/02—Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zeberga et al. | [Retracted] A Novel Text Mining Approach for Mental Health Prediction Using Bi‐LSTM and BERT Model | |
| Parveen et al. | Twitter sentiment analysis using hybrid gated attention recurrent network | |
| Kumar et al. | Systematic literature review of sentiment analysis on Twitter using soft computing techniques | |
| Atoum | Cyberbullying detection through sentiment analysis | |
| Mahmood et al. | Deep sentiments in roman urdu text using recurrent convolutional neural network model | |
| El Alaoui et al. | A novel adaptable approach for sentiment analysis on big social data | |
| Effrosynidis et al. | A comparison of pre-processing techniques for twitter sentiment analysis | |
| Nisha et al. | A comparative analysis of machine learning approaches in personality prediction using MBTI | |
| Atoum | Detecting cyberbullying from tweets through machine learning techniques with sentiment analysis | |
| Faruque et al. | Ascertaining polarity of public opinions on Bangladesh cricket using machine learning techniques | |
| Rajeswari et al. | Sentiment analysis for predicting customer reviews using a hybrid approach | |
| Al Maruf et al. | Hate speech detection in the Bengali language: a comprehensive survey | |
| Pandey et al. | Various aspects of sentiment analysis: a review | |
| Atoum | Cyberbullying detection neural networks using sentiment analysis | |
| Khan et al. | A review on sentiment analysis of twitter data using machine learning techniques | |
| Keerthiga et al. | Machine learning-based depression prediction using social media feeds | |
| Gudumotu et al. | A survey on deep learning models to detect hate speech and bullying in social media | |
| Kumar et al. | Social media analysis for sentiment classification using gradient boosting machines | |
| Das et al. | Enhancing sentiment analysis accuracy on social media comments using a tuned BERT model | |
| Taghandiki et al. | Types of Approaches, Applications and Challenges in the Development of Sentiment Analysis Systems | |
| Kaur | Analyzing twitter feeds to facilitate crises informatics and disaster response during mass emergencies | |
| Nandan et al. | Sentiment Analysis of Twitter Classification by Applying Hybrid-Based Techniques | |
| Gupta et al. | LSTM network for suicide detection | |
| Najadat et al. | Analyzing social media opinions using data analytics | |
| Sabri et al. | A Review for Arabic Extremism Detection Using Machine Learning |