@INPROCEEDINGS{Etaiwi20-COMPSAC-ConsensusMobileApps,
   AUTHOR       = {Mashael (Layan) Etaiwi and Sylvie Hamel and 
      Yann-Ga�l Gu�h�neuc},
   BOOKTITLE    = {Proceedings of the 44<sup>th</sup> Computer Software and Applications Conference (COMPSAC)},
   TITLE        = {Order in Chaos: Prioritizing Mobile App Reviews using 
      Consensus Algorithms},
   YEAR         = {2020},
   OPTADDRESS   = {},
   OPTCROSSREF  = {},
   EDITOR       = {Wing Kwong Chan and Bill Claycomb and Hiroki Takakura},
   MONTH        = {July},
   NOTE         = {9 pages.},
   OPTNUMBER    = {},
   OPTORGANIZATION = {},
   OPTPAGES     = {},
   PUBLISHER    = {IEEE CS Press},
   OPTSERIES    = {},
   OPTVOLUME    = {},
   KEYWORDS     = {Topic: <b>Requirements and features</b>, 
      Venue: <c>COMPSAC</c>},
   URL          = {http://www.ptidej.net/publications/documents/COMPSAC20.doc.pdf},
   ABSTRACT     = {The continuous growth of the mobile apps industry 
      creates a competition among apps developers. To succeed, app 
      developers must attract and retain users. User reviews provide a 
      wealth of information about bugs to fix and features to add and can 
      help app developers offer high-quality apps. However, apps may 
      receive hundreds of unstructured reviews, which makes transforming 
      them into change requests a difficult task. Approaches exist for 
      analyzing and extracting topics from mobile app reviews, however, 
      prioritizing these reviews has not gained much attention. In this 
      study, we introduce the use of a consensus algorithm to help 
      developers prioritize user reviews for the purpose of app evolution. 
      We evaluate the usefulness of our approach and meaningfulness of its 
      consensus rankings on four Android apps. We compare the rankings 
      against reviews ranked by app developers manually and show that there 
      is a strong correlation between the two (average Kendall rank 
      correlation coefficient = 0.516). Thus, our approach can prioritize 
      user reviews and help developers focus their time/effort on improving 
      their apps instead of on identifying reviews to address in the next 
      release.}
}

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(.","Hamel, S.","Gu�h�neuc, Y."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["Mashael","(Layan)"],"propositions":[],"lastnames":["Etaiwi"],"suffixes":[]},{"firstnames":["Sylvie"],"propositions":[],"lastnames":["Hamel"],"suffixes":[]},{"firstnames":["Yann-Ga�l"],"propositions":[],"lastnames":["Gu�h�neuc"],"suffixes":[]}],"booktitle":"Proceedings of the 44^th Computer Software and Applications Conference (COMPSAC)","title":"Order in Chaos: Prioritizing Mobile App Reviews using Consensus Algorithms","year":"2020","optaddress":"","optcrossref":"","editor":[{"firstnames":["Wing","Kwong"],"propositions":[],"lastnames":["Chan"],"suffixes":[]},{"firstnames":["Bill"],"propositions":[],"lastnames":["Claycomb"],"suffixes":[]},{"firstnames":["Hiroki"],"propositions":[],"lastnames":["Takakura"],"suffixes":[]}],"month":"July","note":"9 pages.","optnumber":"","optorganization":"","optpages":"","publisher":"IEEE CS Press","optseries":"","optvolume":"","keywords":"Topic: <b>Requirements and features</b>, Venue: <c>COMPSAC</c>","url":"http://www.ptidej.net/publications/documents/COMPSAC20.doc.pdf","abstract":"The continuous growth of the mobile apps industry creates a competition among apps developers. To succeed, app developers must attract and retain users. User reviews provide a wealth of information about bugs to fix and features to add and can help app developers offer high-quality apps. However, apps may receive hundreds of unstructured reviews, which makes transforming them into change requests a difficult task. Approaches exist for analyzing and extracting topics from mobile app reviews, however, prioritizing these reviews has not gained much attention. In this study, we introduce the use of a consensus algorithm to help developers prioritize user reviews for the purpose of app evolution. We evaluate the usefulness of our approach and meaningfulness of its consensus rankings on four Android apps. We compare the rankings against reviews ranked by app developers manually and show that there is a strong correlation between the two (average Kendall rank correlation coefficient = 0.516). Thus, our approach can prioritize user reviews and help developers focus their time/effort on improving their apps instead of on identifying reviews to address in the next release.","bibtex":"@INPROCEEDINGS{Etaiwi20-COMPSAC-ConsensusMobileApps,\r\n AUTHOR = {Mashael (Layan) Etaiwi and Sylvie Hamel and \r\n Yann-Ga�l Gu�h�neuc},\r\n BOOKTITLE = {Proceedings of the 44^th Computer Software and Applications Conference (COMPSAC)},\r\n TITLE = {Order in Chaos: Prioritizing Mobile App Reviews using \r\n Consensus Algorithms},\r\n YEAR = {2020},\r\n OPTADDRESS = {},\r\n OPTCROSSREF = {},\r\n EDITOR = {Wing Kwong Chan and Bill Claycomb and Hiroki Takakura},\r\n MONTH = {July},\r\n NOTE = {9 pages.},\r\n OPTNUMBER = {},\r\n OPTORGANIZATION = {},\r\n OPTPAGES = {},\r\n PUBLISHER = {IEEE CS Press},\r\n OPTSERIES = {},\r\n OPTVOLUME = {},\r\n KEYWORDS = {Topic: <b>Requirements and features</b>, \r\n Venue: <c>COMPSAC</c>},\r\n URL = {http://www.ptidej.net/publications/documents/COMPSAC20.doc.pdf},\r\n ABSTRACT = {The continuous growth of the mobile apps industry \r\n creates a competition among apps developers. To succeed, app \r\n developers must attract and retain users. User reviews provide a \r\n wealth of information about bugs to fix and features to add and can \r\n help app developers offer high-quality apps. However, apps may \r\n receive hundreds of unstructured reviews, which makes transforming \r\n them into change requests a difficult task. Approaches exist for \r\n analyzing and extracting topics from mobile app reviews, however, \r\n prioritizing these reviews has not gained much attention. In this \r\n study, we introduce the use of a consensus algorithm to help \r\n developers prioritize user reviews for the purpose of app evolution. \r\n We evaluate the usefulness of our approach and meaningfulness of its \r\n consensus rankings on four Android apps. We compare the rankings \r\n against reviews ranked by app developers manually and show that there \r\n is a strong correlation between the two (average Kendall rank \r\n correlation coefficient = 0.516). Thus, our approach can prioritize \r\n user reviews and help developers focus their time/effort on improving \r\n their apps instead of on identifying reviews to address in the next \r\n release.}\r\n}\r\n\r\n","author_short":["Etaiwi, M. (.","Hamel, S.","Gu�h�neuc, Y."],"editor_short":["Chan, W. K.","Claycomb, B.","Takakura, H."],"key":"Etaiwi20-COMPSAC-ConsensusMobileApps","id":"Etaiwi20-COMPSAC-ConsensusMobileApps","bibbaseid":"etaiwi-hamel-guhneuc-orderinchaosprioritizingmobileappreviewsusingconsensusalgorithms-2020","role":"author","urls":{"Paper":"http://www.ptidej.net/publications/documents/COMPSAC20.doc.pdf"},"keyword":["Topic: <b>Requirements and features</b>","Venue: <c>COMPSAC</c>"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"http://www.yann-gael.gueheneuc.net/Work/Publications/Biblio/complete-bibliography.bib","dataSources":["8vn5MSGYWB4fAx9Z4"],"keywords":["topic: <b>requirements and features</b>","venue: <c>compsac</c>"],"search_terms":["order","chaos","prioritizing","mobile","app","reviews","using","consensus","algorithms","etaiwi","hamel","gu�h�neuc"],"title":"Order in Chaos: Prioritizing Mobile App Reviews using Consensus Algorithms","year":2020}