Emerging topics in app reviews highlight the topics(e.g.,software bugs)with which users are concerned during certain periods.Identifying emerging topics accurately,and in a timely manner,could help developers more eff...Emerging topics in app reviews highlight the topics(e.g.,software bugs)with which users are concerned during certain periods.Identifying emerging topics accurately,and in a timely manner,could help developers more effectively update apps.Methods for identifying emerging topics in app reviews based on topic models or clustering methods have been proposed in the literature.However,the accuracy of emerging topic identification is reduced because reviews are short in length and offer limited information.To solve this problem,an improved emerging topic identification(IETI)approach is proposed in this work.Specifically,we adopt natural language processing techniques to reduce noisy data,and identify emerging topics in app reviews using the adaptive online biterm topic model.Then we interpret the implicature of emerging topics through relevant phrases and sentences.We adopt the official app changelogs as ground truth,and evaluate IETI in six common apps.The experimental results indicate that IETI is more accurate than the baseline in identifying emerging topics,with improvements in the F1 score of 0.126 for phrase labels and 0.061 for sentence labels.Finally,we release the codes of IETI on Github(https://github.com/wanizhou/IETI).展开更多
The production-oriented approach(POA)has been developed over a decade.It is driven by the need to improve English classroom instruction for university students in China(Wen,2016).It is also motivated by the aspiration...The production-oriented approach(POA)has been developed over a decade.It is driven by the need to improve English classroom instruction for university students in China(Wen,2016).It is also motivated by the aspiration to enhance the quality of foreign language education in other similar pedagogical contexts outside China.A volume of research has been done by Wen Qiufang and her research team,to formulate the展开更多
基金Project supported by the Anhui Provincial Natural Science Foundation of China(No.1908085MF183)the National Natural Science Foundation of China(Nos.62002084and 61976005)+4 种基金the Training Program for Young and MiddleAged Top Talents of Anhui Polytechnic University,China(No.201812)the Zhejiang Provincial Natural Science Foundation of China(No.LQ21F020004)the State Key Laboratory for Novel Software Technology(Nanjing University)Research Program,China(No.KFKT2019B23)the Open Research Fund of Anhui Key Laboratory of Detection Technology and Energy Saving Devices,Anhui Polytechnic University,China(No.DTESD2020B03)the Stable Support Plan for Colleges and Universities in Shenzhen,China(No.GXWD20201230155427003-20200730101839009)。
文摘Emerging topics in app reviews highlight the topics(e.g.,software bugs)with which users are concerned during certain periods.Identifying emerging topics accurately,and in a timely manner,could help developers more effectively update apps.Methods for identifying emerging topics in app reviews based on topic models or clustering methods have been proposed in the literature.However,the accuracy of emerging topic identification is reduced because reviews are short in length and offer limited information.To solve this problem,an improved emerging topic identification(IETI)approach is proposed in this work.Specifically,we adopt natural language processing techniques to reduce noisy data,and identify emerging topics in app reviews using the adaptive online biterm topic model.Then we interpret the implicature of emerging topics through relevant phrases and sentences.We adopt the official app changelogs as ground truth,and evaluate IETI in six common apps.The experimental results indicate that IETI is more accurate than the baseline in identifying emerging topics,with improvements in the F1 score of 0.126 for phrase labels and 0.061 for sentence labels.Finally,we release the codes of IETI on Github(https://github.com/wanizhou/IETI).
文摘The production-oriented approach(POA)has been developed over a decade.It is driven by the need to improve English classroom instruction for university students in China(Wen,2016).It is also motivated by the aspiration to enhance the quality of foreign language education in other similar pedagogical contexts outside China.A volume of research has been done by Wen Qiufang and her research team,to formulate the