ILiAD:从 Twitter 帖子中获取语言注释数据的交互式语料库

Simon Gonzalez
{"title":"ILiAD:从 Twitter 帖子中获取语言注释数据的交互式语料库","authors":"Simon Gonzalez","doi":"arxiv-2407.15374","DOIUrl":null,"url":null,"abstract":"Social Media platforms have offered invaluable opportunities for linguistic\nresearch. The availability of up-to-date data, coming from any part in the\nworld, and coming from natural contexts, has allowed researchers to study\nlanguage in real time. One of the fields that has made great use of social\nmedia platforms is Corpus Linguistics. There is currently a wide range of\nprojects which have been able to successfully create corpora from social media.\nIn this paper, we present the development and deployment of a linguistic corpus\nfrom Twitter posts in English, coming from 26 news agencies and 27 individuals.\nThe main goal was to create a fully annotated English corpus for linguistic\nanalysis. We include information on morphology and syntax, as well as NLP\nfeatures such as tokenization, lemmas, and n- grams. The information is\npresented through a range of powerful visualisations for users to explore\nlinguistic patterns in the corpus. With this tool, we aim to contribute to the\narea of language technologies applied to linguistic research.","PeriodicalId":501285,"journal":{"name":"arXiv - CS - Digital Libraries","volume":"430 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ILiAD: An Interactive Corpus for Linguistic Annotated Data from Twitter Posts\",\"authors\":\"Simon Gonzalez\",\"doi\":\"arxiv-2407.15374\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Social Media platforms have offered invaluable opportunities for linguistic\\nresearch. The availability of up-to-date data, coming from any part in the\\nworld, and coming from natural contexts, has allowed researchers to study\\nlanguage in real time. One of the fields that has made great use of social\\nmedia platforms is Corpus Linguistics. There is currently a wide range of\\nprojects which have been able to successfully create corpora from social media.\\nIn this paper, we present the development and deployment of a linguistic corpus\\nfrom Twitter posts in English, coming from 26 news agencies and 27 individuals.\\nThe main goal was to create a fully annotated English corpus for linguistic\\nanalysis. We include information on morphology and syntax, as well as NLP\\nfeatures such as tokenization, lemmas, and n- grams. The information is\\npresented through a range of powerful visualisations for users to explore\\nlinguistic patterns in the corpus. With this tool, we aim to contribute to the\\narea of language technologies applied to linguistic research.\",\"PeriodicalId\":501285,\"journal\":{\"name\":\"arXiv - CS - Digital Libraries\",\"volume\":\"430 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Digital Libraries\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2407.15374\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Digital Libraries","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.15374","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

社交媒体平台为语言研究提供了宝贵的机会。来自世界任何地方和自然语境的最新数据使研究人员能够实时研究语言。语料库语言学是充分利用社交媒体平台的领域之一。在本文中,我们介绍了从 26 家新闻机构和 27 位个人的 Twitter 英语帖子中开发和部署语言语料库的情况。我们的主要目标是创建用于语言分析的全注释英语语料库,其中包括词法和句法信息,以及标记化、词组和 n- grams 等 NLP 特征。这些信息通过一系列功能强大的可视化展示出来,供用户探索语料库中的语言模式。通过这一工具,我们希望为语言技术应用于语言学研究领域做出贡献。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
ILiAD: An Interactive Corpus for Linguistic Annotated Data from Twitter Posts
Social Media platforms have offered invaluable opportunities for linguistic research. The availability of up-to-date data, coming from any part in the world, and coming from natural contexts, has allowed researchers to study language in real time. One of the fields that has made great use of social media platforms is Corpus Linguistics. There is currently a wide range of projects which have been able to successfully create corpora from social media. In this paper, we present the development and deployment of a linguistic corpus from Twitter posts in English, coming from 26 news agencies and 27 individuals. The main goal was to create a fully annotated English corpus for linguistic analysis. We include information on morphology and syntax, as well as NLP features such as tokenization, lemmas, and n- grams. The information is presented through a range of powerful visualisations for users to explore linguistic patterns in the corpus. With this tool, we aim to contribute to the area of language technologies applied to linguistic research.
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
自引率
0.00%
发文量
0
期刊最新文献
Publishing Instincts: An Exploration-Exploitation Framework for Studying Academic Publishing Behavior and "Home Venues" Research Citations Building Trust in Wikipedia Evaluating the Linguistic Coverage of OpenAlex: An Assessment of Metadata Accuracy and Completeness Towards understanding evolution of science through language model series Ensuring Adherence to Standards in Experiment-Related Metadata Entered Via Spreadsheets
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1