{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T13:45:51Z","timestamp":1765547151414,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":24,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T00:00:00Z","timestamp":1697846400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["SWIFT 2030249"],"award-info":[{"award-number":["SWIFT 2030249"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Sichuan Province, China","award":["2022NSFSC0505"],"award-info":[{"award-number":["2022NSFSC0505"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072077 and 62176043"],"award-info":[{"award-number":["62072077 and 62176043"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,21]]},"DOI":"10.1145\/3583780.3615124","type":"proceedings-article","created":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T07:45:42Z","timestamp":1697874342000},"page":"5417-5421","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["MDCC: A Multimodal Dynamic Dataset for Donation-based Crowdfunding Campaigns"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6415-7558","authenticated-orcid":false,"given":"Xovee","family":"Xu","sequence":"first","affiliation":[{"name":"University of Electronic Science and Technology of China & Kash Institute of Electronics and Information Industry, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2526-4823","authenticated-orcid":false,"given":"Jiayang","family":"Li","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8038-8150","authenticated-orcid":false,"given":"Fan","family":"Zhou","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China & Kash Institute of Electronics and Information Industry, Chengdu, China"}]}],"member":"320","published-online":{"date-parts":[[2023,10,21]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Reward-based Crowdfunding Success Prediction with Multimodal Data. AMCIS","author":"Bao Liqian","year":"2022","unstructured":"Liqian Bao , Zongxi Liu , and Huimin Zhao . 2022. Reward-based Crowdfunding Success Prediction with Multimodal Data. AMCIS ( 2022 ). Liqian Bao, Zongxi Liu, and Huimin Zhao. 2022. Reward-based Crowdfunding Success Prediction with Multimodal Data. AMCIS (2022)."},{"key":"e_1_3_2_1_2_1","volume-title":"Extracting Image Characteristics to Predict Crowdfunding Success. arXiv:2203.14806","author":"Blanchard Simon J","year":"2022","unstructured":"Simon J Blanchard , Theodore J Noseworthy , Ethan Pancer , and Maxwell Poole . 2022. Extracting Image Characteristics to Predict Crowdfunding Success. arXiv:2203.14806 ( 2022 ). Simon J Blanchard, Theodore J Noseworthy, Ethan Pancer, and Maxwell Poole. 2022. Extracting Image Characteristics to Predict Crowdfunding Success. arXiv:2203.14806 (2022)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Chaoran Cheng Fei Tan Xiurui Hou and Zhi Wei. 2019. Success Prediction on Crowdfunding with Multimodal Deep Learning.. In IJCAI. 2158--2164. Chaoran Cheng Fei Tan Xiurui Hou and Zhi Wei. 2019. Success Prediction on Crowdfunding with Multimodal Deep Learning.. In IJCAI. 2158--2164.","DOI":"10.24963\/ijcai.2019\/299"},{"key":"e_1_3_2_1_4_1","volume-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv:1412.3555","author":"Chung Junyoung","year":"2014","unstructured":"Junyoung Chung , Caglar Gulcehre , KyungHyun Cho , and Yoshua Bengio . 2014. Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv:1412.3555 ( 2014 ). Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio. 2014. Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv:1412.3555 (2014)."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40854-022-00345-6"},{"key":"e_1_3_2_1_6_1","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin , Ming-Wei Chang , Kenton Lee , and Kristina Toutanova . 2018 . BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv:1810.04805 (2018). Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_1_7_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In CVPR. 770--778. Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In CVPR. 770--778."},{"key":"e_1_3_2_1_8_1","unstructured":"Jian-Ren Hou Jie Zhang and Kunpeng Zhang. 2019. Can title images predict the emotions and the performance of crowdfunding projects?. In HICSS. Jian-Ren Hou Jie Zhang and Kunpeng Zhang. 2019. Can title images predict the emotions and the performance of crowdfunding projects?. In HICSS."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1609\/icwsm.v15i1.18055"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.socscimed.2021.114105"},{"key":"e_1_3_2_1_11_1","unstructured":"Kickstarter. 2023. Kickstarter Stats. https:\/\/www.kickstarter.com\/help\/stats Accessed: 2023-06--15. Kickstarter. 2023. Kickstarter Stats. https:\/\/www.kickstarter.com\/help\/stats Accessed: 2023-06--15."},{"key":"e_1_3_2_1_12_1","volume-title":"Less Than 12% Reach Goals. Forbes (5","author":"Lee Bruce Y.","year":"2022","unstructured":"Bruce Y. Lee . 2022. Most GoFundMe Campaigns For Medical Bills Fail , Less Than 12% Reach Goals. Forbes (5 Feb 2022 ). https:\/\/www.forbes.com\/sites\/brucelee\/2022\/02\/05\/most-gofundme-campaigns-for-medical-bills-fail-less-than-12-reach-goals Bruce Y. Lee. 2022. Most GoFundMe Campaigns For Medical Bills Fail, Less Than 12% Reach Goals. Forbes (5 Feb 2022). https:\/\/www.forbes.com\/sites\/brucelee\/2022\/02\/05\/most-gofundme-campaigns-for-medical-bills-fail-less-than-12-reach-goals"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"crossref","unstructured":"Qi Liu Guifeng Wang Hongke Zhao Chuanren Liu Tong Xu and Enhong Chen. 2017. Enhancing Campaign Design in Crowdfunding: A Product Supply Optimization Perspective.. In IJCAI. 695--702. Qi Liu Guifeng Wang Hongke Zhao Chuanren Liu Tong Xu and Enhong Chen. 2017. Enhancing Campaign Design in Crowdfunding: A Product Supply Optimization Perspective.. In IJCAI. 695--702.","DOI":"10.24963\/ijcai.2017\/97"},{"key":"e_1_3_2_1_14_1","unstructured":"Asmaa Mirkhan. 2020. BlurryFaces: A tool to blur faces or other regions in images and videos. https:\/\/github.com\/asmaamirkhan\/BlurryFaces. GitHub repository. Asmaa Mirkhan. 2020. BlurryFaces: A tool to blur faces or other regions in images and videos. https:\/\/github.com\/asmaamirkhan\/BlurryFaces. GitHub repository."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Tanushree Mitra and Eric Gilbert. 2014. The language that gets people to give: Phrases that predict success on Kickstarter. In CSCW. 49--61. Tanushree Mitra and Eric Gilbert. 2014. The language that gets people to give: Phrases that predict success on Kickstarter. In CSCW. 49--61.","DOI":"10.1145\/2531602.2531656"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbusvent.2013.06.005"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Xiaoying Ren Linli Xu Tianxiang Zhao Chen Zhu Junliang Guo and Enhong Chen. 2018. Tracking and forecasting dynamics in crowdfunding: A basis-synthesis approach. In ICDM. 1212--1217. Xiaoying Ren Linli Xu Tianxiang Zhao Chen Zhu Junliang Guo and Enhong Chen. 2018. Tracking and forecasting dynamics in crowdfunding: A basis-synthesis approach. In ICDM. 1212--1217.","DOI":"10.1109\/ICDM.2018.00161"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3141256"},{"key":"e_1_3_2_1_19_1","volume-title":"NIPS","volume":"30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani , Noam Shazeer , Niki Parmar , Jakob Uszkoreit , Llion Jones , Aidan N Gomez , \u0141ukasz Kaiser , and Illia Polosukhin . 2017 . Attention is all you need . NIPS , Vol. 30 (2017). Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. NIPS , Vol. 30 (2017)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107839"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109740"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"crossref","unstructured":"Hongke Zhao Hefu Zhang Yong Ge Qi Liu Enhong Chen Huayu Li and Le Wu. 2017. Tracking the dynamics in crowdfunding. In SIGKDD. 625--634. Hongke Zhao Hefu Zhang Yong Ge Qi Liu Enhong Chen Huayu Li and Le Wu. 2017. Tracking the dynamics in crowdfunding. In SIGKDD. 625--634.","DOI":"10.1145\/3097983.3098030"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783401"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3433000"}],"event":{"name":"CIKM '23: The 32nd ACM International Conference on Information and Knowledge Management","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Birmingham United Kingdom","acronym":"CIKM '23"},"container-title":["Proceedings of the 32nd ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3583780.3615124","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3583780.3615124","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3583780.3615124","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:36:42Z","timestamp":1750178202000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3583780.3615124"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,21]]},"references-count":24,"alternative-id":["10.1145\/3583780.3615124","10.1145\/3583780"],"URL":"https:\/\/doi.org\/10.1145\/3583780.3615124","relation":{},"subject":[],"published":{"date-parts":[[2023,10,21]]},"assertion":[{"value":"2023-10-21","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}