Data Pub Date : 2023-11-28 DOI: 10.3390/data8120180

Yankang Su, Zbigniew J. Kabala

{"title":"Public Perception of ChatGPT and Transfer Learning for Tweets Sentiment Analysis Using Wolfram Mathematica","authors":"Yankang Su, Zbigniew J. Kabala","doi":"10.3390/data8120180","DOIUrl":"https://doi.org/10.3390/data8120180","url":null,"abstract":"Understanding public opinion on ChatGPT is crucial for recognizing its strengths and areas of concern. By utilizing natural language processing (NLP), this study delves into tweets regarding ChatGPT to determine temporal patterns, content features, and topic modeling and perform a sentiment analysis. Analyzing a dataset of 500,000 tweets, our research shifts from conventional data science tools like Python and R to exploit Wolfram Mathematica’s robust capabilities. Additionally, with the aim of solving the problem of ignoring semantic information in the LDA model feature extraction, a synergistic methodology entwining LDA, GloVe embeddings, and K-Nearest Neighbors (KNN) clustering is proposed to categorize topics within ChatGPT-related tweets. This comprehensive strategy ensures semantic, syntactic, and topical congruence within classified groups by utilizing the strengths of probabilistic modeling, semantic embeddings, and similarity-based clustering. While built-in sentiment classifiers often fall short in accuracy, we introduce four transfer learning techniques from the Wolfram Neural Net Repository to address this gap. Two of these techniques involve transferring static word embeddings, “GloVe” and “ConceptNet”, which are further processed using an LSTM layer. The remaining techniques center on fine-tuning pre-trained models using scantily annotated data; one refines embeddings from language models (ELMo), while the other fine-tunes bidirectional encoder representations from transformers (BERT). Our experiments on the dataset underscore the effectiveness of the four methods for the sentiment analysis of tweets. This investigation augments our comprehension of user sentiment towards ChatGPT and emphasizes the continued significance of exploration in this domain. Furthermore, this work serves as a pivotal reference for scholars who are accustomed to using Wolfram Mathematica in other research domains, aiding their efforts in text analytics on social media platforms.","PeriodicalId":502371,"journal":{"name":"Data","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139221366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

In Vivo Drug Testing during Embryonic Wound Healing: Establishing the Avian Model 胚胎伤口愈合期间的体内药物测试：建立禽类模型

Data Pub Date : 2023-11-25 DOI: 10.3390/data8120178

Martin Bablok, Beate Brand-Saberi, Morris Gellisch, Gabriela Morosan-Puopolo

{"title":"In Vivo Drug Testing during Embryonic Wound Healing: Establishing the Avian Model","authors":"Martin Bablok, Beate Brand-Saberi, Morris Gellisch, Gabriela Morosan-Puopolo","doi":"10.3390/data8120178","DOIUrl":"https://doi.org/10.3390/data8120178","url":null,"abstract":"The relevance of identifying pathological processes in the context of embryonic development is increasingly gaining attention in terms of professionalized prenatal care. To analyze local effects of prenatally administered drugs during embryonic development, the model organism of the chicken embryo can be used in a first exploratory approach. For the examination of local dexamethasone administration—as an exemplary drug—common bead implantation protocols have been adapted to serve as an in vivo technique for local drug testing during embryonic skin regeneration. For this, acrylic beads were soaked in a dexamethasone solution and implanted into skin incisional wounds of 4-day-old chicken embryos. After further incubation, the effects of the applied substance on the process of embryonic skin regeneration were analyzed using histological and molecular biological techniques. This data descriptor contains a detailed microsurgical protocol, a representative video demonstration, and exemplary results of local glucocorticoid-induced changes during embryonic wound healing. To conclude, this method allows for the analysis of the local effects of a particular substance on a cellular level and can be extended to serve as an in vivo technique for numerous other drugs to be tested on embryonic tissue.","PeriodicalId":502371,"journal":{"name":"Data","volume":"114 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139236958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Long-Term Spatiotemporal Oceanographic Data from the Northeast Pacific Ocean: 1980–2022 Reconstruction Based on the Korea Oceanographic Data Center (KODC) Dataset 东北太平洋的长期时空海洋学数据：基于韩国海洋数据中心（KODC）数据集的 1980-2022 年重建图

Data Pub Date : 2023-11-23 DOI: 10.3390/data8120175

Seong-Hyeon Kim, Hansoo Kim

{"title":"Long-Term Spatiotemporal Oceanographic Data from the Northeast Pacific Ocean: 1980–2022 Reconstruction Based on the Korea Oceanographic Data Center (KODC) Dataset","authors":"Seong-Hyeon Kim, Hansoo Kim","doi":"10.3390/data8120175","DOIUrl":"https://doi.org/10.3390/data8120175","url":null,"abstract":"The Korea Oceanographic Data Center (KODC), overseen by the National Institute of Fisheries Science (NIFS), is a pivotal hub for collecting, processing, and disseminating marine science data. By digitizing and subjecting observational data to rigorous quality control, the KODC ensures accurate information in line with international standards. The center actively engages in global partnerships and fosters marine data exchange. A wide array of marine information is provided through the KODC website, including observational metadata, coastal oceanographic data, real-time buoy records, and fishery environmental data. Coastal oceanographic observational data from 207 stations across various sea regions have been collected biannually since 1961. This dataset covers 14 standard water depths; includes essential parameters, such as temperature, salinity, nutrients, and pH; serves as the foundation for news, reports, and analyses by the NIFS; and is widely employed to study seasonal and regional marine variations, with researchers supplementing the limited data for comprehensive insights. The dataset offers information for each water depth at a 1 m interval over 1980–2022, facilitating research across disciplines. Data processing, including interpolation and quality control, is based on MATLAB. These data are classified by region and accessible online; hence, researchers can easily explore spatiotemporal trends in marine environments.","PeriodicalId":502371,"journal":{"name":"Data","volume":"124 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139243255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Model Design and Applied Methodology in Geothermal Simulations in Very Low Enthalpy for Big Data Applications 面向大数据应用的极低焓地热模拟中的模型设计和应用方法

Data Pub Date : 2023-11-23 DOI: 10.3390/data8120176

Roberto Arranz-Revenga, María Pilar Dorrego de Luxán, Juan Herrera Herbert, Luis Enrique García Cambronero

{"title":"Model Design and Applied Methodology in Geothermal Simulations in Very Low Enthalpy for Big Data Applications","authors":"Roberto Arranz-Revenga, María Pilar Dorrego de Luxán, Juan Herrera Herbert, Luis Enrique García Cambronero","doi":"10.3390/data8120176","DOIUrl":"https://doi.org/10.3390/data8120176","url":null,"abstract":"Low-enthalpy geothermal installations for heating, air conditioning, and domestic hot water are gaining traction due to efforts towards energy decarbonization. This article is part of a broader research project aimed at employing artificial intelligence and big data techniques to develop a predictive system for the thermal behavior of the ground in very low-enthalpy geothermal applications. In this initial article, a summarized process is outlined to generate large quantities of synthetic data through a ground simulation method. The proposed theoretical model allows simulation of the soil’s thermal behavior using an electrical equivalent. The electrical circuit derived is loaded into a simulation program along with an input function representing the system’s thermal load pattern. The simulator responds with another function that calculates the values of the ground over time. Some examples of value conversion and the utility of the input function system to encode thermal loads during simulation are demonstrated. It bears the limitation of invalidity in the presence of underground water currents. Model validation is pending, and once defined, a corresponding testing plan will be proposed for its validation.","PeriodicalId":502371,"journal":{"name":"Data","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139245364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biodiversity of Terrestrial Testate Amoebae in Western Siberia Lowland Peatlands 西西伯利亚低地泥炭地陆生睾丸变形虫的生物多样性

Data Pub Date : 2023-11-17 DOI: 10.3390/data8110173

D. Saldaev, K. Babeshko, V. Chernyshov, Anton Esaulov, Xiuyuan Gu, Nikita Kriuchkov, N. Mazei, Nailia Saldaeva, Jiahui Su, A. Tsyganov, Basil Yakimov, Svetlana Yushkovets, Yu. A. Mazei

引用次数: 0

Testate Amoebae (Amphitremida, Arcellinida, Euglyphida) in Sphagnum Bogs: The Dataset from Eastern Fennoscandia 泥炭沼泽中的睾丸变形虫（Amphitremida、Arcellinida、Euglyphida）：来自东芬诺斯康迪亚的数据集

Data Pub Date : 2023-11-15 DOI: 10.3390/data8110172

A. Ivanovskii, K. Babeshko, V. Chernyshov, Anton Esaulov, Aleksandr Komarov, Elena Malysheva, N. Mazei, Diana Meskhadze, D. Saldaev, A. Tsyganov, Yu. A. Mazei

引用次数: 0

ChatGPT across Arabic Twitter: A Study of Topics, Sentiments, and Sarcasm 阿拉伯语推特上的 ChatGPT：关于话题、情感和讽刺的研究

Data Pub Date : 2023-11-14 DOI: 10.3390/data8110171

Shahad Al-Khalifa, Fatima Alhumaidhi, Hind Alotaibi, Hend Suliman Al-Khalifa

{"title":"ChatGPT across Arabic Twitter: A Study of Topics, Sentiments, and Sarcasm","authors":"Shahad Al-Khalifa, Fatima Alhumaidhi, Hind Alotaibi, Hend Suliman Al-Khalifa","doi":"10.3390/data8110171","DOIUrl":"https://doi.org/10.3390/data8110171","url":null,"abstract":"While ChatGPT has gained global significance and widespread adoption, its exploration within specific cultural contexts, particularly within the Arab world, remains relatively limited. This study investigates the discussions among early Arab users in Arabic tweets related to ChatGPT, focusing on topics, sentiments, and the presence of sarcasm. Data analysis and topic-modeling techniques were employed to examine 34,760 Arabic tweets collected using specific keywords. This study revealed a strong interest within the Arabic-speaking community in ChatGPT technology, with prevalent discussions spanning various topics, including controversies, regional relevance, fake content, and sector-specific dialogues. Despite the enthusiasm, concerns regarding ethical risks and negative implications of ChatGPT’s emergence were highlighted, indicating apprehension toward advanced artificial intelligence (AI) technology in language generation. Region-specific discussions underscored the diverse adoption of AI applications and ChatGPT technology. Sentiment analysis of the tweets demonstrated a predominantly neutral sentiment distribution (92.8%), suggesting a focus on objectivity and factuality over emotional expression. The prevalence of neutral sentiments indicated a preference for evidence-based reasoning and logical arguments, fostering constructive discussions influenced by cultural norms. Sarcasm was found in 4% of the tweets, distributed across various topics but not dominating the conversation. This study’s implications include the need for AI developers to address ethical concerns and the importance of educating users about the technology’s ethical considerations and risks. Policymakers should consider the regional relevance and potential scams, emphasizing the necessity for ethical guidelines and regulations.","PeriodicalId":502371,"journal":{"name":"Data","volume":"49 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139276137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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