基于N-gram的土耳其日报twitter账号识别方法

2017 International Artificial Intelligence and Data Processing Symposium (IDAP) Pub Date : 2017-09-01 DOI:10.1109/IDAP.2017.8090209

İslam Mayda, Mirsat Yesiltepe

{"title":"基于N-gram的土耳其日报twitter账号识别方法","authors":"İslam Mayda, Mirsat Yesiltepe","doi":"10.1109/IDAP.2017.8090209","DOIUrl":null,"url":null,"abstract":"Twitter is one of the most popular social media networks in the world. It is also mostly used by corporate companies, media as well as individual users. Media organizations use Twitter to announce about the news. Although the language of the given news is formal and preferred words to share information are different for each organization. In this study, we proposed an approach to recognize the Twitter accounts of Turkish daily newspapers. Our approach is based on character 3-grams and word 2-grams for digitizing the texts. In order to classify the information, we performed the experiments on several classifiers and found that Sequential Minimal Optimization (SMO) outperformed other algorithms. We carried out the experiments on the real-dataset of Twitter accounts of Turkish daily newspapers and classified them accurately more than 98%.1","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"N-gram based approach to recognize the twitter accounts of Turkish daily newspapers\",\"authors\":\"İslam Mayda, Mirsat Yesiltepe\",\"doi\":\"10.1109/IDAP.2017.8090209\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Twitter is one of the most popular social media networks in the world. It is also mostly used by corporate companies, media as well as individual users. Media organizations use Twitter to announce about the news. Although the language of the given news is formal and preferred words to share information are different for each organization. In this study, we proposed an approach to recognize the Twitter accounts of Turkish daily newspapers. Our approach is based on character 3-grams and word 2-grams for digitizing the texts. In order to classify the information, we performed the experiments on several classifiers and found that Sequential Minimal Optimization (SMO) outperformed other algorithms. We carried out the experiments on the real-dataset of Twitter accounts of Turkish daily newspapers and classified them accurately more than 98%.1\",\"PeriodicalId\":111721,\"journal\":{\"name\":\"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IDAP.2017.8090209\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IDAP.2017.8090209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

摘要

Twitter是世界上最受欢迎的社交媒体网络之一。它也主要被公司、媒体和个人用户使用。媒体组织使用Twitter来宣布这一消息。虽然给定的新闻语言是正式的，但每个组织分享信息的首选词是不同的。在本研究中，我们提出了一种识别土耳其日报Twitter账户的方法。我们的方法是基于字符3克和单词2克来实现文本的数字化。为了对信息进行分类，我们在几种分类器上进行了实验，发现顺序最小优化(SMO)优于其他算法。我们在土耳其日报Twitter账户的真实数据集上进行了实验，分类准确率超过98% 1

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

N-gram based approach to recognize the twitter accounts of Turkish daily newspapers

Twitter is one of the most popular social media networks in the world. It is also mostly used by corporate companies, media as well as individual users. Media organizations use Twitter to announce about the news. Although the language of the given news is formal and preferred words to share information are different for each organization. In this study, we proposed an approach to recognize the Twitter accounts of Turkish daily newspapers. Our approach is based on character 3-grams and word 2-grams for digitizing the texts. In order to classify the information, we performed the experiments on several classifiers and found that Sequential Minimal Optimization (SMO) outperformed other algorithms. We carried out the experiments on the real-dataset of Twitter accounts of Turkish daily newspapers and classified them accurately more than 98%.1

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2017 International Artificial Intelligence and Data Processing Symposium (IDAP)

自引率

0.00%

发文量