Темир йўл транспорти: долзарб масалалар ва инновациялар 6-том 2-сан (2025) · 86-93-беттер
Data Cleaning and Preprocessing Methods for Automatic Detection of Textual Information in Social Networks: Data Cleaning and Preprocessing Methods for Automatic Detection of Textual Information in Social Networks
Юлдошев, Ю., Отахонова, Б., Обидова, К.
Аннотация
Today, social networks, such as Twitter, Facebook, Instagram and other platforms, have become one of the main means of exchanging information between people. Every day, millions of users interact with various text posts, comments, statuses, and thoughts, from which various information, trends, and conclusions can be drawn. At the same time, texts posted on social networks are often written in informal language, with abbreviations, emojis, vague expressions, and sometimes grammatical errors. This makes it difficult to automatically analyze text data. To effectively analyze text data, it is necessary to clean and preprocess it. The process of cleaning data involves removing unnecessary elements from the text, such as special characters, emoji, stop words, and spelling errors. Preprocessing involves formatting the text for analysis, converting words to their root form, and converting them to lowercase. These processes are important for obtaining accurate results in analyzing texts in social networks.
классификация текстасоциальные сетикороткий текстнеформальный языкобработка естественного языка (NLP)машинное обучениеглубокое обучениетокенстеммингстоп-слово
Метадайындар булагы: журналдын OAI-PMH архиви · Sindex толук текстти сактабайт, булакка шилтеме берет.