Literatura académica sobre el tema "TWITTER DATASET"
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Artículos de revistas sobre el tema "TWITTER DATASET"
Meier, Florian. "TWikiL – the Twitter Wikipedia Link Dataset". Proceedings of the International AAAI Conference on Web and Social Media 16 (31 de mayo de 2022): 1292–301. http://dx.doi.org/10.1609/icwsm.v16i1.19381.
Texto completoAlmalki, Jameel. "A machine learning-based approach for sentiment analysis on distance learning from Arabic Tweets". PeerJ Computer Science 8 (26 de julio de 2022): e1047. http://dx.doi.org/10.7717/peerj-cs.1047.
Texto completoDar, Momna, Faiza Iqbal, Rabia Latif, Ayesha Altaf y Nor Shahida Mohd Jamail. "Policy-Based Spam Detection of Tweets Dataset". Electronics 12, n.º 12 (14 de junio de 2023): 2662. http://dx.doi.org/10.3390/electronics12122662.
Texto completoFerragina, Paolo, Francesco Piccinno y Roberto Santoro. "On Analyzing Hashtags in Twitter". Proceedings of the International AAAI Conference on Web and Social Media 9, n.º 1 (3 de agosto de 2021): 110–19. http://dx.doi.org/10.1609/icwsm.v9i1.14584.
Texto completoThakur, Nirmalya. "MonkeyPox2022Tweets: A Large-Scale Twitter Dataset on the 2022 Monkeypox Outbreak, Findings from Analysis of Tweets, and Open Research Questions". Infectious Disease Reports 14, n.º 6 (14 de noviembre de 2022): 855–83. http://dx.doi.org/10.3390/idr14060087.
Texto completoGamal, Donia, Marco Alfonse, El-Sayed M.El-Horbaty y Abdel-Badeeh M.Salem. "Twitter Benchmark Dataset for Arabic Sentiment Analysis". International Journal of Modern Education and Computer Science 11, n.º 1 (8 de enero de 2019): 33–38. http://dx.doi.org/10.5815/ijmecs.2019.01.04.
Texto completoAguilar-Gallegos, Norman, Leticia Elizabeth Romero-García, Enrique Genaro Martínez-González, Edgar Iván García-Sánchez y Jorge Aguilar-Ávila. "Dataset on dynamics of Coronavirus on Twitter". Data in Brief 30 (junio de 2020): 105684. http://dx.doi.org/10.1016/j.dib.2020.105684.
Texto completoGuo, Xiaobo y Soroush Vosoughi. "A Large-Scale Longitudinal Multimodal Dataset of State-Backed Information Operations on Twitter". Proceedings of the International AAAI Conference on Web and Social Media 16 (31 de mayo de 2022): 1245–50. http://dx.doi.org/10.1609/icwsm.v16i1.19375.
Texto completoNia, Zahra Movahedi, Ali Ahmadi, Bruce Mellado, Jianhong Wu, James Orbinski, Ali Asgary y Jude D. Kong. "Twitter-based gender recognition using transformers". Mathematical Biosciences and Engineering 20, n.º 9 (2023): 15957–77. http://dx.doi.org/10.3934/mbe.2023711.
Texto completoSagarika, Namasani, Bommadi Sreenija Reddy, Vanka Varshitha, Kodavati Geetanjali, N. V. Ganapathi Raju y Latha Kunaparaju. "Sarcasm Discernment on Social Media Platform". E3S Web of Conferences 309 (2021): 01037. http://dx.doi.org/10.1051/e3sconf/202130901037.
Texto completoTesis sobre el tema "TWITTER DATASET"
YADAV, DEEPIKA. "SENTIMENT ANALYSIS ON TWITTER DATA". Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2020. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18821.
Texto completoКохан, Василь Володимир Богданович y Vasyl Volodymyr Kokhan. "Алгоритмічне та програмне забезпечення систем автоматизованого оцінювання емоційного нахилу статей про Україну". Master's thesis, Тернопільський національний технічний університет імені Івана Пулюя, 2021. http://elartu.tntu.edu.ua/handle/lib/36642.
Texto completoThe aim of the work is to research and develop an algorithm and software for automated sentiment analysis of articles from the social microblogs network Twitter. Section 1 describes algorithms for determining the sentiment of texts, analysis tools available online, and approaches to collecting data for analysis. Section 2 describes the process of gaining access to the Twitter API, approaches to data collection for analysis, and analyzes existing algorithms for sentiment analysis of texts. In section 3, data was collected for evaluation via Twitter API, was developed an algorithm for cleaning data from redundant elements and implemented in the code, and an algorithm for sentiment analysis of texts was developed and implemented as well. Section 4 describes the main requirements for the operation of the software implementation of the algorithm for automated sentiment analysis of articles about Ukraine, in accordance with state sanitary rules and regulations for working with visual display terminals of electronic computers DSanPIN 3.3.2.007-98.
ВСТУП 9 РОЗДІЛ 1 АНАЛІЗ ПРЕДМЕТНОЇ ОБЛАСТІ ТА ОГЛЯД АЛГОРИТМІВ ДЛЯ ВИЗНАЧЕННЯ ЕМОЦІЙНОГО НАХИЛУ ТЕКСТІВ 11 1.1. Оцінка емоційного нахилу текстів 11 1.2. Аналіз інструментів та публікацій на тему аналізу емоційного нахилу 14 1.3. Підходи до збору даних для аналізу емоційного нахилу текстів 18 1.4. Висновки розділу 1 23 РОЗДІЛ 2 РОЗРОБКА АЛГОРИТМУ ОЦІНКИ ЕМОЦІЙНОГО НАХИЛУ СТАТТЕЙ НОВИН 25 2.1. Процес отримання доступу до Твіттер АПІ 25 2.2. Звернення до Твіттер АПІ 28 2.3. Аналіз даних 32 2.4. Висновки розділу 2 33 РОЗДІЛ 3 ПРАКТИЧНА РЕАЛІЗАЦІЯ АЛГОРИТМУ ТА ДОСЛІДЖЕННЯ АНАЛІЗУ ЕМОЦІЙНОГО НАХИЛУ ТЕКСТУ 34 3.1. Процес збору даних 34 3.2. Підготовка даних до аналізу 36 3.3. Оцінювання емоційного нахилу текстів 40 3.4. Висновки розділу 3 46 РОЗДІЛ 4 ОХОРОНА ПРАЦІ ТА БЕЗПЕКА В НАДЗВИЧАЙНИХ СИТУАЦІЯХ 47 4.1. Охорона праці 47 4.2. Забезпечення безпеки життєдіяльності при роботі з ПК 49 ВИСНОВКИ 52 ПЕРЕЛІК ПОСИЛАНЬ 53 ДОДАТОК А 57 ДОДАТОК Б 64 ДОДАТОК В 65
Björck, Olof. "Creating Interactive Visualizations for Twitter Datasets using D3". Thesis, Uppsala universitet, Matematiska institutionen, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-351802.
Texto completoProject Meme Evolution Programme
Libros sobre el tema "TWITTER DATASET"
Shi, Feng. Learn About Encodings in R With Data From How ISIS Uses Twitter Dataset (2016). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526488633.
Texto completoShi, Feng. Learn About Encodings in Python With Data From How ISIS Uses Twitter Dataset (2016). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526497857.
Texto completoShi, Feng. Learn About Regular Expressions in R With Data From How ISIS Uses Twitter Dataset (2016). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526488824.
Texto completoShi, Feng. Learn About Regular Expressions in Python With Data From How ISIS Uses Twitter Dataset (2016). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526497871.
Texto completoShi, Feng. Learn About Text Pre-Processing in R With Data From How ISIS Uses Twitter Dataset (2016). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526488909.
Texto completoShi, Feng. Learn About Text Pre-Processing in Python With Data From How ISIS Uses Twitter Dataset (2016). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526497864.
Texto completoShi, Feng. Learn About Basic Concepts in Text Analysis in R With Data From How ISIS Uses Twitter Dataset (2016). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526488626.
Texto completoShi, Feng. Learn About Basic Concepts in Text Analysis in Python With Data From How ISIS Uses Twitter Dataset (2016). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526497796.
Texto completoShi, Feng. Learn About Term Frequency–Inverse Document Frequency in Text Analysis in R With Data From How ISIS Uses Twitter Dataset (2016). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526489012.
Texto completoShi, Feng. Learn About Term Frequency–Inverse Document Frequency in Text Analysis in Python With Data From How ISIS Uses Twitter Dataset (2016). 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2019. http://dx.doi.org/10.4135/9781526498038.
Texto completoCapítulos de libros sobre el tema "TWITTER DATASET"
Mukhopadhyay, Debajyoti, Kirti Mishra, Kriti Mishra y Laxmi Tiwari. "Cyber Bullying Detection Based on Twitter Dataset". En Machine Learning for Predictive Analysis, 87–94. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7106-0_9.
Texto completoNandy, Hiran y Rajeswari Sridhar. "Filtering-Based Text Sentiment Analysis for Twitter Dataset". En Advances in Intelligent Systems and Computing, 1035–46. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3514-7_77.
Texto completoKumar, Yogesh, Sameeka Saini, Harendra Sharma, Ritu Payal y Arpit Mishra. "Feedback Investigation on Twitter Dataset Using Classification Approaches". En Proceedings of International Conference on Recent Trends in Computing, 251–62. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7118-0_22.
Texto completoLlewellyn, Clare, Claire Grover, Beatrice Alex, Jon Oberlander y Richard Tobin. "Extracting a Topic Specific Dataset from a Twitter Archive". En Research and Advanced Technology for Digital Libraries, 364–67. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24592-8_36.
Texto completoThorburn, Joshua, Javier Torregrosa y Ángel Panizo. "Measuring Extremism: Validating an Alt-Right Twitter Accounts Dataset". En Intelligent Data Engineering and Automated Learning – IDEAL 2018, 9–14. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03496-2_2.
Texto completoGupta, Shelley, Archana Singh y Jayanthi Ranjan. "An Online Document Emoji-Based Classification Using Twitter Dataset". En Proceedings of Data Analytics and Management, 409–17. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-6285-0_33.
Texto completoWijesiriwardene, Thilini, Hale Inan, Ugur Kursuncu, Manas Gaur, Valerie L. Shalin, Krishnaprasad Thirunarayan, Amit Sheth y I. Budak Arpinar. "ALONE: A Dataset for Toxic Behavior Among Adolescents on Twitter". En Lecture Notes in Computer Science, 427–39. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60975-7_31.
Texto completoNair, Vinita y Jyoti Pareek. "Evaluation of Supervised Classifiers for Fake News Detection Using Twitter Dataset". En Springer Proceedings in Mathematics & Statistics, 435–46. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-15175-0_36.
Texto completoMathews, Deepa Mary y Sajimon Abraham. "Twitter Data Sentiment Analysis on a Malayalam Dataset Using Rule-Based Approach". En Emerging Research in Computing, Information, Communication and Applications, 407–15. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6001-5_33.
Texto completoUniyal, Deepak y Amit Agarwal. "IRLCov19: A Large COVID-19 Multilingual Twitter Dataset of Indian Regional Languages". En Communications in Computer and Information Science, 309–24. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-93733-1_22.
Texto completoActas de conferencias sobre el tema "TWITTER DATASET"
Saputri, Mei Silviana, Rahmad Mahendra y Mirna Adriani. "Emotion Classification on Indonesian Twitter Dataset". En 2018 International Conference on Asian Language Processing (IALP). IEEE, 2018. http://dx.doi.org/10.1109/ialp.2018.8629262.
Texto completoJonker, Richard Adolph Aires, Roshan Poudel, Olga Fajarda, Sérgio Matos, José Luís Oliveira y Rui Pedro Lopes. "Portuguese Twitter Dataset on COVID-19". En 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2022. http://dx.doi.org/10.1109/asonam55673.2022.10068592.
Texto completoPutra, Oddy Virgantara, Fathin Muhammad Wasmanson, Triana Harmini y Shoffin Nahwa Utama. "Sundanese Twitter Dataset for Emotion Classification". En 2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia (CENIM). IEEE, 2020. http://dx.doi.org/10.1109/cenim51130.2020.9297929.
Texto completoRahutomo, Reza, Arif Budiarto, Kartika Purwandari, Anzaludin Samsinga Perbangsa, Tjeng Wawan Cenggoro y Bens Pardamean. "Ten-Year Compilation of #SaveKPK Twitter Dataset". En 2020 International Conference on Information Management and Technology (ICIMTech). IEEE, 2020. http://dx.doi.org/10.1109/icimtech50083.2020.9211246.
Texto completoSalem, Marwa S., Sally S. Ismail y Mostafa Aref. "Personality Traits for Egyptian Twitter Users Dataset". En ICSIE '19: 2019 8th International Conference on Software and Information Engineering. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3328833.3328851.
Texto completoWagh, Rasika y Payal Punde. "Survey on Sentiment Analysis using Twitter Dataset". En 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA). IEEE, 2018. http://dx.doi.org/10.1109/iceca.2018.8474783.
Texto completoSquire, Megan. "Apache-affiliated Twitter screen names: A dataset". En 2013 10th IEEE Working Conference on Mining Software Repositories (MSR 2013). IEEE, 2013. http://dx.doi.org/10.1109/msr.2013.6624043.
Texto completoSahu, Lokesh y Bhavesh Shah. "An Emotion based Sentiment Analysis on Twitter Dataset". En 2022 IEEE International Conference on Current Development in Engineering and Technology (CCET). IEEE, 2022. http://dx.doi.org/10.1109/ccet56606.2022.10079995.
Texto completoZumma, Md Thoufiq, Jerin Akther Munia, Dipankar Halder y Md Sadekur Rahman. "Personality Prediction from Twitter Dataset using Machine Learning". En 2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2022. http://dx.doi.org/10.1109/icccnt54827.2022.9984495.
Texto completoManolescu, Mihai y Çağrı Çöltekin. "ROFF - A Romanian Twitter Dataset for Offensive Language". En International Conference Recent Advances in Natural Language Processing. INCOMA Ltd. Shoumen, BULGARIA, 2021. http://dx.doi.org/10.26615/978-954-452-072-4_102.
Texto completoInformes sobre el tema "TWITTER DATASET"
Warin, Thierry. The World Health Organization in a Post-COVID-19 Era: An Exploration of Public Engagement on Twitter. CIRANO, junio de 2022. http://dx.doi.org/10.54932/ehuh4224.
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