{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T19:31:12Z","timestamp":1769283072055,"version":"3.49.0"},"reference-count":48,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T00:00:00Z","timestamp":1750982400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Suzhou Key Laboratory of Artificial Intelligence and Social Governance Technologies","award":["SZS2023007"],"award-info":[{"award-number":["SZS2023007"]}]},{"name":"Suzhou Key Laboratory of Artificial Intelligence and Social Governance Technologies","award":["YZCXPT2023101"],"award-info":[{"award-number":["YZCXPT2023101"]}]},{"name":"Suzhou Key Laboratory of Artificial Intelligence and Social Governance Technologies","award":["CJRH2024101"],"award-info":[{"award-number":["CJRH2024101"]}]},{"name":"Smart Social Governance Technology and Innovative Application Platform","award":["SZS2023007"],"award-info":[{"award-number":["SZS2023007"]}]},{"name":"Smart Social Governance Technology and Innovative Application Platform","award":["YZCXPT2023101"],"award-info":[{"award-number":["YZCXPT2023101"]}]},{"name":"Smart Social Governance Technology and Innovative Application Platform","award":["CJRH2024101"],"award-info":[{"award-number":["CJRH2024101"]}]},{"name":"The Innovation System of the Integration between Industry and Education for Smart Governance","award":["SZS2023007"],"award-info":[{"award-number":["SZS2023007"]}]},{"name":"The Innovation System of the Integration between Industry and Education for Smart Governance","award":["YZCXPT2023101"],"award-info":[{"award-number":["YZCXPT2023101"]}]},{"name":"The Innovation System of the Integration between Industry and Education for Smart Governance","award":["CJRH2024101"],"award-info":[{"award-number":["CJRH2024101"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Accurately predicting the success of startup financing is critical for strategic business planning and informed investor decision-making. Traditional financing prediction models typically focus on a company\u2019s financial indicators to explore the impact of factors such as resource allocation and strategic choices on financing success, yet they often overlook the important role of social media as an external source of information in influencing financing performance. To address this gap, this paper focuses on the role of social media sentiment in predicting startup financing success and proposes a decision support system (DSS) framework that integrates multi-source data. Specifically, this study combines financial data from the Crunchbase platform with company-related social media news data from Twitter. The BERTweet model is used to perform sentiment analysis on the social media texts, extracting sentiment features such as polarity and intensity to capture public attitudes and expectations toward the company. Subsequently, financial indicators, social media numerical features, and sentiment features are combined to construct a decision support system for predicting financing success using a deep neural network (DNN). Experimental results show that the decision support system incorporating social media data significantly outperforms traditional decision support systems in prediction accuracy, with sentiment features further enhancing the model\u2019s ability to identify a company\u2019s financing performance. Our study provides strong support for understanding the profound influence of public sentiment, offering practical guidance for startups to optimize financing strategies and for investors to make informed decisions.<\/jats:p>","DOI":"10.3390\/systems13070520","type":"journal-article","created":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T13:06:17Z","timestamp":1751288777000},"page":"520","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Enhancing Startup Financing Success Prediction Based on Social Media Sentiment"],"prefix":"10.3390","volume":"13","author":[{"given":"Zhen","family":"Qiu","sequence":"first","affiliation":[{"name":"School of Economics and Management, University of the Chinese Academy of Sciences, Beijing 100090, China"}]},{"given":"Yifan","family":"Qu","sequence":"additional","affiliation":[{"name":"School of Information, Renmin University of China, Beijing 100872, China"}]},{"given":"Shaochen","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Information, Renmin University of China, Beijing 100872, China"},{"name":"Department of Information Systems, City University of Hong Kong, Hong Kong, China"}]},{"given":"Wuji","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information, Renmin University of China, Beijing 100872, China"}]},{"given":"Wei","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Information, Renmin University of China, Beijing 100872, China"}]},{"given":"Hong","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Economics and Management, University of the Chinese Academy of Sciences, Beijing 100090, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,27]]},"reference":[{"key":"ref_1","first-page":"356","article-title":"Deep Learning to Predict Start-Up Business Success","volume":"15","author":"Hsairi","year":"2024","journal-title":"Int. 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