B-TTDb: A Database of Turkish Tweets for Predicting the Top One Hundred Emojis

IF 4.7 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-07-24 DOI:10.1145/3681783
Y. Bi̇ti̇ri̇m
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引用次数: 0

Abstract

Emoji prediction is an important research task that focuses on finding the most appropriate emoji(s) quickly and effortlessly for a specific text. Now that Turkish is on the list of the top 20 most spoken languages in the world and there are a considerable number of Turkish-speaking social media users, studying emoji prediction in Turkish holds significant value. In this study, a Turkish tweets database, named Bitirim's Turkish Tweets Database (B-TTDb), was constructed for academic and industrial studies based on the prediction of the top 100 emojis. B-TTDb consists of four datasets. The first dataset includes raw tweets, the second dataset is the organized version of the first dataset, the third dataset is the pre-processed version of the second dataset, and the last one is the organized version of the third dataset. The last one is the final version and it is named Bitirim's Dataset (B-D). It includes a total of 158,201 unique tweets belonging to the top 100 emoji classes. For database validation, experiments were conducted on B-D with popular machine learning algorithms for the top 10, 20, 50, and 100 emojis. This study could be considered as the first study that contributes to the literature by the first validated large database of Turkish tweets that includes such a large number of emojis. In addition, B-TTDb could be a basis as well as motivation for various further studies.
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B-TTDb:用于预测百大表情符号的土耳其推文数据库
表情符号预测是一项重要的研究任务,其重点是为特定文本快速、轻松地找到最合适的表情符号。目前,土耳其语已跻身世界上使用人数最多的 20 种语言之列,而且有相当数量的土耳其语社交媒体用户,因此研究土耳其语中的表情符号预测具有重要价值。在本研究中,基于对前 100 个表情符号的预测,构建了一个土耳其语推文数据库,名为 Bitirim 的土耳其语推文数据库(B-TTDb),用于学术和工业研究。B-TTDb 由四个数据集组成。第一个数据集包括原始推文,第二个数据集是第一个数据集的整理版,第三个数据集是第二个数据集的预处理版,最后一个数据集是第三个数据集的整理版。最后一个是最终版本,被命名为 Bitirim 数据集(B-D)。该数据集共包含 158201 条属于前 100 个表情符号类别的独特推文。为了验证数据库,使用流行的机器学习算法在 B-D 上对前 10、20、50 和 100 个表情符号进行了实验。这项研究可以说是土耳其推文大型数据库的首次验证,其中包含了大量的表情符号,是对文献的首次贡献。此外,B-TTDb 可以作为各种进一步研究的基础和动力。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
期刊介绍: ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.
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