UX-RIVIS: Visualization of information about UX data based on app reviews
Resumo
Information Visualization (InfoVis) provides techniques and methods for interactive visual representations to enhance human understanding of data. This facilitates monitoring and makes relevant information accessible to all users, regardless of their experience in data analysis. Software professionals in mobile development have shown interest in using visual representations (e.g., charts, tables) to support the analysis of user reviews of applications available in app stores. However, analysis tools often focus on data mining resources and do not provide appropriate visualizations for the target audience (i.e., mobile software professionals). Considering the context previously described, this paper presents the main results of a dissertation project. In this project, a set of 16 guidelines was proposed to support the design of UX data visualizations. The guidelines were conceived from a Systematic Literature Mapping (SLM) that explored 21 papers from academic literature. These papers were analyzed to extract the guidelines in the form of recommendations. The guidelines, along with Shneiderman’s seminal work `Visual Information-Seeking Mantra’, were utilized to develop a proposed UX data visualization named User eXperience Reviews Information Visualization (UX-RIVIS). Shneiderman’s mantra allowed for the introduction of levels of navigation, which produced visualizations ranging from data overview to detailed data. UX-RIVIS visualizations were evaluated by 23 software professionals using the method of Intermediate Semiotic Inspection (i.e., a qualitative approach for assessment). The evaluation provided results that examined the communicability and perceptiveness of software professionals regarding the ease of use of the visualizations. The results indicated the usefulness of the visualizations provided by UX-RIVIS for software professionals in data analysis. It was also noted that these professionals preferred certain visualizations, such as tables and pie charts. Moreover, participants showed interest in using the visualizations for their work activities.
Referências
Elsa Bakiu and Emitza Guzman. 2017. Which feature is unusable? Detecting usability and user experience issues from user reviews. In 2017 IEEE 25th international requirements engineering conference workshops (REW). IEEE, 182–187.
Regina Bernhaupt, Célia Martinie, Philippe Palanque, and Gunter Wallner. 2020. A generic visualization approach supporting task-based evaluation of usability and user experience. In Human-Centered Software Engineering: 8th IFIP WG 13.2 International Working Conference, HCSE 2020, Eindhoven, The Netherlands, November 30–December 2, 2020, Proceedings 8. Springer, 24–44.
Stuart K Card, Jock Mackinlay, and Ben Shneiderman. 1999. Readings in information visualization: using vision to think. Morgan Kaufmann.
Ning Chen, Jialiu Lin, Steven CH Hoi, Xiaokui Xiao, and Boshen Zhang. 2014. ARminer: mining informative reviews for developers from mobile app marketplace. In Proceedings of the 36th international conference on software engineering. 767– 778.
B. Craft and P. Cairns. 2005. Beyond guidelines: what can we learn from the visual information seeking mantra?. In Ninth International Conference on Information Visualisation (IV’05). 110–118. DOI: 10.1109/IV.2005.28
Roberto Yuri da Silva Franco, Rodrigo Santos do Amor Divino Lima, Rafael do Monte Paixão, Carlos Gustavo Resque dos Santos, and Bianchi Serique Meiguins. 2019. Uxmood—a sentiment analysis and information visualization tool to support the evaluation of usability and user experience. Information 10, 12 (2019), 366.
Erica Rodrigues de Oliveira and Raquel Oliveira Prates. 2018. Intermediated semiotic inspection method. In Proceedings of the 17th Brazilian Symposium on Human Factors in Computing Systems. 1–10.
Clarisse Sieckenius De Souza. 2005. The semiotic engineering of human-computer interaction. MIT press.
Clarisse Sickenius de Souza and Carla Faria Leitão. 2009. Semiotic engineering methods for scientific research in HCI. Morgan & Claypool Publishers.
Roberto Yuri Da Silva Franco, Alexandre Abreu De Freitas, Rodrigo Santos Do Amor Divino Lima, Marcelle Pereira Mota, Carlos Gustavo Resque Dos Santos, and Bianchi Serique Meiguins. 2019. UXmood-A tool to investigate the user experience (UX) based on multimodal Sentiment analysis and information visualization (InfoVis). In 2019 23rd International Conference Information Visualisation (IV). IEEE, 175–180.
Bin Fu, Jialiu Lin, Lei Li, Christos Faloutsos, Jason Hong, and Norman Sadeh. 2013. Why people hate your app: Making sense of user feedback in a mobile app store. In Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining. 1276–1284.
Cuiyun Gao, Baoxiang Wang, Pinjia He, Jieming Zhu, Yangfan Zhou, and Michael R Lyu. 2015. Paid: Prioritizing app issues for developers by tracking user reviews over versions. In 2015 IEEE 26th international symposium on software reliability engineering (ISSRE). IEEE, 35–45.
Cuiyun Gao, Jichuan Zeng, Michael R Lyu, and Irwin King. 2018. Online app review analysis for identifying emerging issues. In Proceedings of the 40th International Conference on Software Engineering. 48–58.
G Geetha, Monisha Mittal, K Mohana Prasad, and J Godwin Ponsam. 2022. Interpretation and Analysis of Angular Framework. In 2022 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS). IEEE, 1–6.
Xiaodong Gu and Sunghun Kim. 2015. “what parts of your apps are loved by users?”(T). In 2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 760–770.
Emitza Guzman, Padma Bhuvanagiri, and Bernd Bruegge. 2014. Fave: Visualizing user feedback for software evolution. In 2014 Second IEEE working conference on software visualization. IEEE, 167–171.
Steffen Hedegaard and Jakob Grue Simonsen. 2013. Extracting usability and user experience information from online user reviews. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 2089–2098.
Staffs Keele et al. 2007. Guidelines for performing systematic literature reviews in software engineering.
Maylon Macedo., Gabriel Teixeira., Ariel Campos., and Luciana Zaina. 2024. Supporting User-Centered Requirements Elicitation from Lean Personas: A UX Data Visualization-Based Approach. In Proceedings of the 26th International Conference on Enterprise Information Systems Volume 2: ICEIS. INSTICC, SciTePress, 461–472. DOI: 10.5220/0012567400003690
Tamara Munzner. 2014. Visualization analysis and design. CRC press.
Walter T Nakamura, Edson César C. de Oliveira, Elaine HT de Oliveira, and Tayana Conte. 2023. Ux-mapper: a user experience method to analyze app store reviews. In Proceedings of the XXII Brazilian Symposium on Human Factors in Computing Systems. 1–11.
Erica R Oliveira, Luiz CS Luz, and Raquel O Prates. 2008. Aplicação semiestruturada do método de inspeção semiótica: estudo de caso para o domínio educacional. In Proceedings of the VIII Brazilian Symposium on Human Factors in Computing Systems. 50–59.
Dennis Pagano and Bernd Bruegge. 2013. User involvement in software evolution practice: A case study. In 2013 35th International Conference on Software Engineering (ICSE). IEEE, 953–962.
Ingrid Pettersson, Florian Lachner, Anna-Katharina Frison, Andreas Riener, and Andreas Butz. 2018. A Bermuda triangle? A Review of method application and triangulation in user experience evaluation. In Proceedings of the 2018 CHI conference on human factors in computing systems. 1–16.
Minh Vu Phong, Tam The Nguyen, Hung Viet Pham, and Tung Thanh Nguyen. 2015. Mining user opinions in mobile app reviews: A keyword-based approach (t). In 2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 749–759.
Raquel O Prates, Clarisse S De Souza, and Simone DJ Barbosa. 2000. Methods and tools: a method for evaluating the communicability of user interfaces. interactions 7, 1 (2000), 31–38.
Shibli Saleheen and Wei Lai. 2018. UIWGViz: An architecture of user interestbased web graph vizualization. Journal of Visual Languages & Computing 44 (2018), 39–57.
Faiz Ali Shah, Kairit Sirts, and Dietmar Pfahl. 2019. Using app reviews for competitive analysis: tool support. In Proceedings of the 3rd ACM SIGSOFT International Workshop on App Market Analytics. 40–46.
Ben Shneiderman. 1996. The eyes have it: A task by data type taxonomy for information visualizations. In Proceedings 1996 IEEE symposium on visual languages. IEEE, 336–343.
Colin Ware. 2019. Information visualization: perception for design. Morgan Kaufmann.
Shuo-Yu Yang, Wen Huei Chou, and Han-Xing Chen. 2020. Development of the automated tool to perform analysis and visualisation of user reviews. International Journal of Arts and Technology 12, 3 (2020), 218–237.
