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Media + - Sentiment + - Stance + - Emotion +pretty_name: 'LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Content -- Arabic' +size_categories: + - 10K + +capablities_tasks_datasets + +

+ +## LlamaLens +This repo includes scripts needed to run our full pipeline, including data preprocessing and sampling, instruction dataset creation, model fine-tuning, inference and evaluation. + +### Features +- Multilingual support (Arabic, English, Hindi) +- 19 NLP tasks with 52 datasets +- Optimized for news and social media content analysis + +## 📂 Dataset Overview + +### Arabic Datasets + +| **Task** | **Dataset** | **# Labels** | **# Train** | **# Test** | **# Dev** | +|---------------------------|------------------------------|--------------|-------------|------------|-----------| +| Attentionworthiness | CT22Attentionworthy | 9 | 2,470 | 1,186 | 1,071 | +| Checkworthiness | CT24_T1 | 2 | 22,403 | 500 | 1,093 | +| Claim | CT22Claim | 2 | 3,513 | 1,248 | 339 | +| Cyberbullying | ArCyc_CB | 2 | 3,145 | 900 | 451 | +| Emotion | Emotional-Tone | 8 | 7,024 | 2,009 | 1,005 | +| Emotion | NewsHeadline | 7 | 939 | 323 | 160 | +| Factuality | Arafacts | 5 | 4,354 | 1,245 | 623 | +| Factuality | COVID19Factuality | 2 | 3,513 | 988 | 339 | +| Harmful | CT22Harmful | 2 | 2,484 | 1,201 | 1,076 | +| Hate Speech | annotated-hatetweets-4-classes | 4 | 210,526 | 100,565 | 90,544 | +| Hate Speech | OSACT4SubtaskB | 2 | 4,778 | 1,827 | 2,048 | +| News Genre Categorization | ASND | 10 | 74,496 | 21,942 | 11,136 | +| News Genre Categorization | SANADAkhbarona | 7 | 62,210 | 7,824 | 7,824 | +| News Genre Categorization | SANADAlArabiya | 6 | 56,967 | 7,123 | 7,120 | +| News Genre Categorization | SANADAlkhaleej | 7 | 36,391 | 4,550 | 4,550 | +| News Genre Categorization | UltimateDataset | 10 | 133,036 | 38,456 | 19,269 | +| News Credibility | NewsCredibilityDataset | 2 | 8,671 | 2,730 | 1,426 | +| Summarization | xlsum | -- | 37,425 | 4,689 | 4,689 | +| Offensive Language | ArCyc_OFF | 2 | 3,138 | 900 | 450 | +| Offensive Language | OSACT4SubtaskA | 2 | 4,780 | 1,827 | 2,047 | +| Propaganda | ArPro | 2 | 6,002 | 1,326 | 672 | +| Sarcasm | ArSarcasm-v2 | 2 | 8,749 | 2,996 | 3,761 | +| Sentiment | ar_reviews_100k | 3 | 69,998 | 20,000 | 10,000 | +| Sentiment | ArSAS | 4 | 13,883 | 3,976 | 1,987 | +| Stance | Mawqif-Arabic-Stance-main | 2 | 3,162 | 560 | 950 | +| Stance | stance | 3 | 2,652 | 379 | 755 | +| Subjectivity | ThatiAR | 2 | 2,446 | 748 | 467 | + + +## File Format + +Each JSONL file in the dataset follows a structured format with the following fields: + +- `id`: Unique identifier for each data entry. +- `original_id`: Identifier from the original dataset, if available. +- `input`: The original text that needs to be analyzed. +- `output`: The label assigned to the text after analysis. +- `dataset`: Name of the dataset the entry belongs. +- `task`: The specific task type. +- `lang`: The language of the input text. +- `instructions`: A brief set of instructions describing how the text should be labeled. +- `text`: A formatted structure including instructions and response for the task in a conversation format between the system, user, and assistant, showing the decision process. + + +**Example entry in JSONL file:** + +``` +{ + "id": "d1662e29-11cf-45cb-bf89-fa5cd993bc78", + "original_id": "nan", + "input": "الدفاع الجوي السوري يتصدى لهجوم صاروخي على قاعدة جوية في حمص", + "output": "not_claim", + "dataset": "ans-claim", + "task": "Claim detection", + "lang": "ar", + "instructions": "Analyze the given text and label it as 'claim' if it includes a factual statement that can be verified, or 'not_claim' if it's not a checkable assertion. Return only the label without any explanation, justification or additional text.", + "text": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>You are a social media expert providing accurate analysis and insights.<|eot_id|><|start_header_id|>user<|end_header_id|>Analyze the given text and label it as 'claim' if it includes a factual statement that can be verified, or 'not_claim' if it's not a checkable assertion. Return only the label without any explanation, justification or additional text.\ninput: الدفاع الجوي السوري يتصدى لهجوم صاروخي على قاعدة جوية في حمص\nlabel: <|eot_id|><|start_header_id|>assistant<|end_header_id|>not_claim<|eot_id|><|end_of_text|>" +} +``` + + +## 📢 Citation + +If you use this dataset, please cite our paper: + +@article{kmainasi2024llamalensspecializedmultilingualllm, + title={LlamaLens: Specialized Multilingual LLM for Analyzing News and Social Media Content}, + author={Mohamed Bayan Kmainasi and Ali Ezzat Shahroor and Maram Hasanain and Sahinur Rahman Laskar and Naeemul Hassan and Firoj Alam}, + year={2024}, + journal={arXiv preprint arXiv:2410.15308}, + volume={}, + number={}, + pages={}, + url={https://arxiv.org/abs/2410.15308}, + eprint={2410.15308}, + archivePrefix={arXiv}, + primaryClass={cs.CL} +} diff --git a/SANADAkhbarona-news-categorization/dev.json b/SANADAkhbarona-news-categorization/dev.json new file mode 100644 index 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