{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T20:17:25Z","timestamp":1769631445757,"version":"3.49.0"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"6","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J. Comput. Sci. Technol."],"published-print":{"date-parts":[[2017,11]]},"DOI":"10.1007\/s11390-017-1784-1","type":"journal-article","created":{"date-parts":[[2017,12,6]],"date-time":"2017-12-06T08:50:30Z","timestamp":1512550230000},"page":"1076-1089","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["CSLabel: An Approach for Labelling Mobile App Reviews"],"prefix":"10.1007","volume":"32","author":[{"given":"Li","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin-Yue","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ya-Kun","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,12,8]]},"reference":[{"key":"1784_CR1","doi-asserted-by":"crossref","unstructured":"Pagano D, Maalej W. User feedback in the Appstore: An empirical study. In Proc. the 21st IEEE International Requirements Engineering Conference (RE), July 2013, pp.125-134.","DOI":"10.1109\/RE.2013.6636712"},{"key":"1784_CR2","doi-asserted-by":"crossref","unstructured":"Pagano D, Br\u00fcgge B. User involvement in software evolution practice: A case study. In Proc. the 35th International Conference on Software Engineering (ICSE), May 2013, pp.953-962.","DOI":"10.1109\/ICSE.2013.6606645"},{"key":"1784_CR3","doi-asserted-by":"crossref","unstructured":"Maalej W, Nabil H. Bug report, feature request, or simply praise? On automatically classifying app reviews. In Proc. the 23rd IEEE International Requirements Engineering Conference (RE), Aug. 2015, pp.116-125.","DOI":"10.1109\/RE.2015.7320414"},{"key":"1784_CR4","doi-asserted-by":"crossref","unstructured":"Panichella S, Di Sorbo A, Guzman E, Visaggio C A, Canfora G, Gall H C. How can I improve my app? Classifying user reviews for software maintenance and evolution. In Proc. IEEE International Conference on Software Maintenance and Evolution (ICSME), Sept. 29-Oct. 1, 2015, pp.281-290.","DOI":"10.1109\/ICSM.2015.7332474"},{"issue":"3","key":"1784_CR5","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1007\/s10664-015-9375-7","volume":"21","author":"S McIlroy","year":"2016","unstructured":"McIlroy S, Ali N, Khalid H, Hassan A E. Analyzing and automatically labelling the types of user issues that are raised in mobile app reviews. Empirical Software Engineering, 2016, 21(3): 1067-1106.","journal-title":"Empirical Software Engineering"},{"key":"1784_CR6","unstructured":"Maas A L, Daly R E, Pham P T, Huang D, Ng A Y, Potts C. Learning word vectors for sentiment analysis. In Proc. the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Volume 1, June 2011, pp.142-150."},{"key":"1784_CR7","doi-asserted-by":"crossref","unstructured":"Pang B, Lee L. A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. In Proc. the 42nd Annual Meeting on Association for Computational Linguistics, July 2004, pp.271-278.","DOI":"10.3115\/1218955.1218990"},{"key":"1784_CR8","doi-asserted-by":"crossref","unstructured":"Seaman C B, Shull F, Regardie M, Elbert D, Feldmann R L, Guo Y, Godfrey S. Defect categorization: Making use of a decade of widely varying historical data. In Proc. the 2nd ACM-IEEE International Symposium on Empirical Software Engineering and Measurement, Oct. 2008, pp.149-157.","DOI":"10.1145\/1414004.1414030"},{"issue":"4","key":"1784_CR9","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1109\/32.799955","volume":"25","author":"CB Seaman","year":"1999","unstructured":"Seaman C B. Qualitative methods in empirical studies of software engineering. IEEE Transactions on Software Engineering, 1999, 25(4): 557-572.","journal-title":"IEEE Transactions on Software Engineering"},{"issue":"2","key":"1784_CR10","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1037\/0033-2909.86.2.420","volume":"86","author":"PE Shrout","year":"1979","unstructured":"Shrout P E, Fleiss J L. Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin, 1979, 86(2): 420-428.","journal-title":"Psychological Bulletin"},{"key":"1784_CR11","doi-asserted-by":"crossref","unstructured":"Witten I H, Frank E, Hall M A, Pal C J. Data Mining: Practical Machine Learning Tools and Techniques. Morgan Kaufmann, 2016.","DOI":"10.1016\/B978-0-12-804291-5.00010-6"},{"issue":"4","key":"1784_CR12","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1108\/eb026562","volume":"29","author":"G Salton","year":"1973","unstructured":"Salton G, Yang C S. On the specification of term values in automatic indexing. Journal of Documentation, 1973, 29(4): 351-372.","journal-title":"Journal of Documentation"},{"issue":"5","key":"1784_CR13","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1016\/0306-4573(88)90021-0","volume":"24","author":"G Salton","year":"1988","unstructured":"Salton G, Buckley C. Term-weighting approaches in automatic text retrieval. Information Processing & Management, 1988, 24(5): 513-523.","journal-title":"Information Processing & Management"},{"issue":"1","key":"1784_CR14","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1145\/1656274.1656278","volume":"11","author":"M Hall","year":"2009","unstructured":"Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten I H. The WEKA data mining software: An update. ACM SIGKDD Explorations Newsletter, 2009, 11(1): 10-18.","journal-title":"ACM SIGKDD Explorations Newsletter"},{"key":"1784_CR15","doi-asserted-by":"crossref","unstructured":"Tsoumakas G, Katakis I, Vlahavas I. Mining multi-label data. In Data Mining and Knowledge Discovery Handbook, Maimon R L (ed.), Springer, 2009, pp.667-685.","DOI":"10.1007\/978-0-387-09823-4_34"},{"key":"1784_CR16","unstructured":"Elkan C. The foundations of cost-sensitive learning. In Proc. the 17th International Joint Conference on Artificial Intelligence, Volume 17, Aug. 2001, pp.973-978."},{"key":"1784_CR17","doi-asserted-by":"crossref","unstructured":"Dumais S, Platt J, Heckerman D, Sahami M. Inductive learning algorithms and representations for text categorization. In Proc. the 7th International Conference on Information and Knowledge Management, Nov. 1998, pp.148-155.","DOI":"10.1145\/288627.288651"},{"issue":"1","key":"1784_CR18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/505282.505283","volume":"34","author":"F Sebastiani","year":"2002","unstructured":"Sebastiani F. Machine learning in automated text categorization. ACM Computing Surveys (CSUR), 2002, 34(1): 1-47.","journal-title":"ACM Computing Surveys (CSUR)"},{"key":"1784_CR19","doi-asserted-by":"crossref","unstructured":"Platt J. Fast training of support vector machines using sequential minimal optimization. In Advances in Kernel Methods \u2014 Support Vector Learning, Schoelkopf B, Burges C, Smola A (eds.), MIT Press, 1998.","DOI":"10.7551\/mitpress\/1130.003.0016"},{"key":"1784_CR20","doi-asserted-by":"crossref","unstructured":"Seni G, Elder J F. Ensemble Methods in Data Mining: Improving Accuracy Through Combining Predictions. Morgan & Claypool, 2010.","DOI":"10.2200\/S00240ED1V01Y200912DMK002"},{"key":"1784_CR21","doi-asserted-by":"crossref","unstructured":"Harman M, Jia Y, Zhang Y. App store mining and analysis: MSR for app stores. In Proc. the 9th IEEE Working Conference on Mining Software Repositories (MSR), June 2012, pp.108-111.","DOI":"10.1109\/MSR.2012.6224306"},{"key":"1784_CR22","doi-asserted-by":"crossref","unstructured":"Di Sorbo A, Panichella S, Alexandru C V, Shimagaki J, Visaggio C A, Canfora G, Gall H C. What would users change in my app? Summarizing app reviews for recommending software changes. In Proc. the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering, Nov. 2016, pp.499-510.","DOI":"10.1145\/2950290.2950299"},{"key":"1784_CR23","doi-asserted-by":"crossref","unstructured":"Iacob C, Harrison R. Retrieving and analyzing mobile apps feature requests from online reviews. In Proc. the 10th IEEE Working Conference on Mining Software Repositories (MSR), May 2013, pp.41-44.","DOI":"10.1109\/MSR.2013.6624001"},{"key":"1784_CR24","doi-asserted-by":"crossref","unstructured":"Fu B, Lin J, Li L, Faloutsos C, Hong J, Sadeh N. Why people hate your app: Making sense of user feedback in a mobile app store. In Proc. the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 2013, pp.1276-1284.","DOI":"10.1145\/2487575.2488202"},{"key":"1784_CR25","doi-asserted-by":"crossref","unstructured":"Carre\u00f1o L V G, Winbladh K. Analysis of user comments: An approach for software requirements evolution. In Proc. the 35th International Conference on Software Engineering (ICSE), May 2013, pp.582-591.","DOI":"10.1109\/ICSE.2013.6606604"},{"key":"1784_CR26","doi-asserted-by":"crossref","unstructured":"Jo Y, Oh A H. Aspect and sentiment unification model for online review analysis. In Proc. the 4th ACM International Conference on Web Search and Data Mining, Feb. 2011, pp.815-824.","DOI":"10.1145\/1935826.1935932"},{"key":"1784_CR27","doi-asserted-by":"crossref","unstructured":"Guzman E, MaalejW. How do users like this feature? A fine grained sentiment analysis of app reviews. In Proc. the 22nd IEEE International Requirements Engineering Conference (RE), Aug. 2014, pp.153-162.","DOI":"10.1109\/RE.2014.6912257"},{"key":"1784_CR28","unstructured":"Manning C D, Sch\u00fctze H. Foundations of Statistical Natural Language Processing (1st edition). MIT Press, 1999."},{"issue":"12","key":"1784_CR29","doi-asserted-by":"crossref","first-page":"2544","DOI":"10.1002\/asi.21416","volume":"61","author":"M Thelwall","year":"2010","unstructured":"Thelwall M, Buckley K, Paltoglou G, Cai D, Kappas A. Sentiment strength detection in short informal text. Journal of the American Society for Information Science and Technology, 2010, 61(12): 2544-2558.","journal-title":"Journal of the American Society for Information Science and Technology"},{"key":"1784_CR30","first-page":"993","volume":"3","author":"DM Blei","year":"2003","unstructured":"Blei D M, Ng A Y, Jordan M I. Latent Dirichlet allocation. Journal of Machine Learning Research, 2003, 3: 993-1022.","journal-title":"Journal of Machine Learning Research"},{"key":"1784_CR31","doi-asserted-by":"crossref","unstructured":"Chen N, Lin J, Hoi S C, Xiao X, Zhang B. AR-Miner: Mining informative reviews for developers from mobile app marketplace. In Proc. the 36th International Conference on Software Engineering, May 31-June 7, 2014, pp.767-778.","DOI":"10.1145\/2568225.2568263"}],"container-title":["Journal of Computer Science and Technology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11390-017-1784-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,29]],"date-time":"2023-08-29T18:11:42Z","timestamp":1693332702000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11390-017-1784-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11]]},"references-count":31,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2017,11]]}},"alternative-id":["1784"],"URL":"https:\/\/doi.org\/10.1007\/s11390-017-1784-1","relation":{},"ISSN":["1000-9000","1860-4749"],"issn-type":[{"value":"1000-9000","type":"print"},{"value":"1860-4749","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,11]]}}}