{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T17:05:45Z","timestamp":1780074345706,"version":"3.54.0"},"publisher-location":"Singapore","reference-count":43,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819605750","type":"print"},{"value":"9789819605767","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:00:00Z","timestamp":1732665600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:00:00Z","timestamp":1732665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-96-0576-7_30","type":"book-chapter","created":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T06:52:59Z","timestamp":1732603979000},"page":"406-420","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Native vs Non-native Language Prompting: A Comparative Analysis"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-4115-6057","authenticated-orcid":false,"given":"Mohamed Bayan","family":"Kmainasi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8634-2249","authenticated-orcid":false,"given":"Rakif","family":"Khan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3918-7471","authenticated-orcid":false,"given":"Ali Ezzat","family":"Shahroor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4560-5241","authenticated-orcid":false,"given":"Boushra","family":"Bendou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7466-178X","authenticated-orcid":false,"given":"Maram","family":"Hasanain","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7172-1997","authenticated-orcid":false,"given":"Firoj","family":"Alam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,11,27]]},"reference":[{"key":"30_CR1","unstructured":"Abdelali, A., et al.: LAraBench: benchmarking arabic AI with large language models. In: Graham, Y., Purver, M. (eds.) Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 487\u2013520. Association for Computational Linguistics, St. Julian\u2019s (2024)"},{"key":"30_CR2","doi-asserted-by":"crossref","unstructured":"Ahuja, K., et al.: MEGA: multilingual evaluation of generative AI. In: Bouamor, H., Pino, J., Bali, K. (eds.) Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pp. 4232\u20134267. Association for Computational Linguistics, Singapore (2023)","DOI":"10.18653\/v1\/2023.emnlp-main.258"},{"key":"30_CR3","unstructured":"Alam, F., et al.: A survey on multimodal disinformation detection. In: Proceedings of the 29th International Conference on Computational Linguistics. COLING\u00a02022, Gyeongju, pp. 6625\u20136643 (2022)"},{"key":"30_CR4","doi-asserted-by":"crossref","unstructured":"Alam, F., Mubarak, H., Zaghouani, W., Da\u00a0San\u00a0Martino, G., Nakov, P.: Overview of the WANLP 2022 Shared Task on Propaganda Detection in Arabic, pp. 108\u2013118 (2022)","DOI":"10.18653\/v1\/2022.wanlp-1.11"},{"key":"30_CR5","doi-asserted-by":"crossref","unstructured":"Alam, F., et al.: Fighting the COVID-19 infodemic: modeling the perspective of journalists, fact-checkers, social media platforms, policy makers, and the society. In: Findings of the Association for Computational Linguistics: EMNLP 2021, pp. 611\u2013649. Association for Computational Linguistics, Punta Cana (2021)","DOI":"10.18653\/v1\/2021.findings-emnlp.56"},{"key":"30_CR6","doi-asserted-by":"crossref","unstructured":"Bang, Y., et al.: A multitask, multilingual, multimodal evaluation of ChatGPT on reasoning, hallucination, and interactivity. In: Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 675\u2014718. Association for Computational Linguistics, Indonesia (2023)","DOI":"10.18653\/v1\/2023.ijcnlp-main.45"},{"key":"30_CR7","doi-asserted-by":"crossref","unstructured":"Brooke, S.: \u201cCondescending, rude, assholes\u201d: framing gender and hostility on Stack Overflow. In: WALO, pp. 172\u2013180 (2019)","DOI":"10.18653\/v1\/W19-3519"},{"key":"30_CR8","unstructured":"Brown, T.B., et al. Language models are few-shot learners. Adv. Neural Inf. Process. Syst. (2020)"},{"key":"30_CR9","doi-asserted-by":"crossref","unstructured":"Carbonell, J., Goldstein, J.: The use of MMR, diversity-based reranking for reordering documents and producing summaries. In: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 335\u2013336 (1998)","DOI":"10.1145\/290941.291025"},{"key":"30_CR10","unstructured":"Dalvi, F., et al.: LLMeBench: a flexible framework for accelerating LLMs benchmarking. In: Aletras, N., De\u00a0Clercq, O. (eds.) Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pp. 214\u2013222. Association for Computational Linguistics, St. Julians (2024)"},{"key":"30_CR11","doi-asserted-by":"crossref","unstructured":"Davidson, T., Warmsley, D., Macy, M., Weber, I.: Automated hate speech detection and the problem of offensive language. In: Proceedings of the International AAAI Conference on Web and Social Media (AAAI 2017), vol.\u00a011 (2017)","DOI":"10.1609\/icwsm.v11i1.14955"},{"key":"30_CR12","doi-asserted-by":"crossref","unstructured":"Dimitrov, D., et al.: Detecting propaganda techniques in memes. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pp. 6603\u20136617. Association for Computational Linguistics (2021)","DOI":"10.18653\/v1\/2021.acl-long.516"},{"issue":"4","key":"30_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3232676","volume":"51","author":"P Fortuna","year":"2018","unstructured":"Fortuna, P., Nunes, S.: A survey on automatic detection of hate speech in text. ACM Comput. Surv. 51(4), 1\u201330 (2018)","journal-title":"ACM Comput. Surv."},{"key":"30_CR14","unstructured":"Galassi, A., et al.: Overview of the CLEF-2023 CheckThat! lab task 2 on subjectivity in news articles. In: Working Notes of CLEF 2023\u2013Conference and Labs of the Evaluation Forum (CLEF 2023), Thessaloniki (2023)"},{"key":"30_CR15","unstructured":"Gao, H., Chen, Y., Lee, K., Palsetia, D., Choudhary, A.N.: Towards online spam filtering in social networks. In: Network and Distributed System Security Symposium (NDSS 2012), pp. 1\u201316 (2012)"},{"key":"30_CR16","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1162\/tacl_a_00454","volume":"10","author":"Z Guo","year":"2022","unstructured":"Guo, Z., Schlichtkrull, M., Vlachos, A.: A survey on automated fact-checking. Trans. Assoc. Comput. Linguist. 10, 178\u2013206 (2022)","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"30_CR17","unstructured":"Jiao, W., Wang, W., Huang, J.T., Wang, X., Shi, S., Tu, Z.: Is chatgpt a good translator? Yes with gpt-4 as the engine. arXiv preprint arXiv:2301.08745 (2023)"},{"key":"30_CR18","doi-asserted-by":"crossref","unstructured":"Jin, Y., Choi, M., Verma, G., Wang, J., Kumar, S.: Mm-soc: benchmarking multimodal large language models in social media platforms. arXiv preprint arXiv:2402.14154 (2024)","DOI":"10.18653\/v1\/2024.findings-acl.370"},{"key":"30_CR19","doi-asserted-by":"crossref","unstructured":"Joksimovic, S., et al.: Automated identification of verbally abusive behaviors in online discussions. In: WALO, pp. 36\u201345 (2019)","DOI":"10.18653\/v1\/W19-3505"},{"key":"30_CR20","doi-asserted-by":"crossref","unstructured":"Khondaker, M.T.I., Waheed, A., Abdul-Mageed, M., et\u00a0al.: GPTAraEval: a comprehensive evaluation of chatgpt on Arabic NLP. In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pp. 220\u2013247 (2023)","DOI":"10.18653\/v1\/2023.emnlp-main.16"},{"key":"30_CR21","doi-asserted-by":"crossref","unstructured":"Khouja, J.: Stance prediction and claim verification: an Arabic perspective. In: Proceedings of the Third Workshop on Fact Extraction and VERification (FEVER), pp. 8\u201317. Association for Computational Linguistics (2020)","DOI":"10.18653\/v1\/2020.fever-1.2"},{"key":"30_CR22","unstructured":"Konstantinovskiy, L., Price, O., Babakar, M., Zubiaga, A.: Towards automated factchecking: Developing an annotation schema and benchmark for consistent automated claim detection. arXiv preprint arXiv:1809.08193 (2018)"},{"key":"30_CR23","unstructured":"Liang, P., et\u00a0al.: Holistic evaluation of language models. Trans. Mach. Learn. Res."},{"key":"30_CR24","doi-asserted-by":"crossref","unstructured":"Liang, W., Yuksekgonul, M., Mao, Y., Wu, E., Zou, J.: Gpt detectors are biased against non-native English writers. Patterns 4(7), 100779 (2023)","DOI":"10.1016\/j.patter.2023.100779"},{"issue":"9","key":"30_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3560815","volume":"55","author":"P Liu","year":"2023","unstructured":"Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., Neubig, G.: Pre-train, prompt, and predict: a systematic survey of prompting methods in natural language processing. ACM Comput. Surv. 55(9), 1\u201335 (2023)","journal-title":"ACM Comput. Surv."},{"issue":"2","key":"30_CR26","doi-asserted-by":"publisher","first-page":"85","DOI":"10.26599\/BDMA.2019.9020015","volume":"3","author":"MS Mahmud","year":"2020","unstructured":"Mahmud, M.S., Huang, J.Z., Salloum, S., Emara, T.Z., Sadatdiynov, K.: A survey of data partitioning and sampling methods to support big data analysis. Big Data Mining Analyt. 3(2), 85\u2013101 (2020)","journal-title":"Big Data Mining Analyt."},{"key":"30_CR27","doi-asserted-by":"crossref","unstructured":"Marchisio, K., Ko, W.Y., B\u00e9rard, A., Dehaze, T., Ruder, S.: Understanding and mitigating language confusion in LLMS. arXiv preprint arXiv:2406.20052 (2024)","DOI":"10.18653\/v1\/2024.emnlp-main.380"},{"key":"30_CR28","doi-asserted-by":"publisher","first-page":"1219767","DOI":"10.3389\/frai.2023.1219767","volume":"6","author":"H Mubarak","year":"2023","unstructured":"Mubarak, H., Abdaljalil, S., Nassar, A., Alam, F.: Detecting and identifying the reasons for deleted tweets before they are posted. Front. Artif. Intell. 6, 1219767 (2023)","journal-title":"Front. Artif. Intell."},{"key":"30_CR29","doi-asserted-by":"crossref","unstructured":"Mubarak, H., Abdelali, A., Hassan, S., Darwish, K.: Spam detection on Arabic twitter. In: Social Informatics: 12th International Conference, SocInfo 2020, Pisa, 6\u20139 October 2020, Proceedings 12, pp. 237\u2013251. Springer (2020)","DOI":"10.1007\/978-3-030-60975-7_18"},{"key":"30_CR30","unstructured":"Mubarak, H., Darwish, K., Magdy, W., Elsayed, T., Al-Khalifa, H.: Overview of OSACT4 Arabic offensive language detection shared task. In: Proceedings of the 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection, pp. 48\u201352. European Language Resource Association, Marseille (2020)"},{"key":"30_CR31","unstructured":"Mubarak, H., Hassan, S., Abdelali, A.: Adult content detection on Arabic twitter: analysis and experiments. In: Proceedings of the Sixth Arabic Natural Language Processing Workshop, pp. 136\u2013144 (2021)"},{"key":"30_CR32","unstructured":"Nakov, P., et al.: Overview of the CLEF-2022 CheckThat! lab task 1 on identifying relevant claims in tweets. In: Working Notes of CLEF 2022\u2014Conference and Labs of the Evaluation Forum (CLEF\u00a02022) (2022)"},{"key":"30_CR33","doi-asserted-by":"crossref","unstructured":"Nakov, P., et al.: Automated fact-checking for assisting human fact-checkers. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), pp. 4551\u20134558 (2021)","DOI":"10.24963\/ijcai.2021\/619"},{"key":"30_CR34","doi-asserted-by":"crossref","unstructured":"Nguyen, X.P., Aljunied, S.M., Joty, S., Bing, L.: Democratizing LLMS for low-resource languages by leveraging their English dominant abilities with linguistically-diverse prompts. arXiv preprint arXiv:2306.11372 (2023)","DOI":"10.18653\/v1\/2024.acl-long.192"},{"key":"30_CR35","unstructured":"OpenAI: GPT-4 technical report. Tech. rep. OpenAI (2023)"},{"key":"30_CR36","unstructured":"Oshikawa, R., Qian, J., Wang, W.Y.: A survey on natural language processing for fake news detection. In: Proceedings of the Twelfth Language Resources and Evaluation Conference, pp. 6086\u20136093 (2020)"},{"key":"30_CR37","doi-asserted-by":"crossref","unstructured":"Reimers, N., Gurevych, I.: Sentence-BERT: sentence embeddings using Siamese BERT-networks. In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP 2019), Hong Kong, pp. 3982\u20133992 (2019)","DOI":"10.18653\/v1\/D19-1410"},{"key":"30_CR38","unstructured":"Sengupta, N., et\u00a0al.: Jais and jais-chat: Arabic-centric foundation and instruction-tuned open generative large language models. arXiv preprint arXiv:2308.16149 (2023)"},{"key":"30_CR39","doi-asserted-by":"crossref","unstructured":"Shin, T., Razeghi, Y., Logan\u00a0IV, R.L., Wallace, E., Singh, S.: AutoPrompt: eliciting knowledge from language models with automatically generated prompts. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 4222\u20134235 (2020)","DOI":"10.18653\/v1\/2020.emnlp-main.346"},{"key":"30_CR40","unstructured":"Suwaileh, R., Hasanain, M., Hubail, F., Zaghouani, W., Alam, F.: ThatiAR: subjectivity detection in Arabic news sentences. arXiv preprint arXiv:2406.05559 (2024)"},{"key":"30_CR41","unstructured":"Team, L.: The Llama 3 herd of models. arXiv (2023)"},{"key":"30_CR42","unstructured":"Wei, J., et al.: Chain-of-thought prompting elicits reasoning in large language models. In: Proceedings of the 36th International Conference on Neural Information Processing Systems, pp. 24824\u201324837 (2022)"},{"key":"30_CR43","unstructured":"Zhou, Y., et al.: Large language models are human-level prompt engineers. In: NeurIPS 2022 Foundation Models for Decision Making Workshop (2022)"}],"container-title":["Lecture Notes in Computer Science","Web Information Systems Engineering \u2013 WISE 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-0576-7_30","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:28:50Z","timestamp":1733099330000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-0576-7_30"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,27]]},"ISBN":["9789819605750","9789819605767"],"references-count":43,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-0576-7_30","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,27]]},"assertion":[{"value":"27 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"WISE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Web Information Systems Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Doha","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Qatar","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"wise2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/wise2024-qatar.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}