ABSTRACT
Survey research is one of the most used empirical research methods, and it is a means to contribute to theory development. A survey can be exploratory, descriptive, or explanatory. Whatever the objective, it will generate data that may support the construction of a theory or validate it. However, researchers must carefully evaluate data so they can transform them into useful information for science. Little is said about how complex and susceptible to human failures this process can be. We note that all the data analysis work is still highly manual and exhausting for the researcher, who is not always qualified to perform data analysis and, sometimes, can make mistakes in this process, inserting wrong numbers or calculating something wrong. Some existing tools can support this process but do not specifically focus on analyzing survey responses, combining valuable qualitative and quantitative analysis of responses. In this study, we introduce Lyzeli, a tool designed to assist researchers in analyzing and correlating survey responses. The proposed tool aims to deliver automatic detection of question types, sentiment analysis of responses, data filtering, word cloud, word count, graphics, codification for open-based questions answers.
Tool Demonstration: https://youtu.be/e2w4TfhlxBY
- Ahmad Nauman Ghazi, Kai Petersen, Sri Sai Vijay Raj Reddy, and Harini Nekkanti. 2019. Survey Research in Software Engineering: Problems and Mitigation Strategies. IEEE Access 7(2019), 24703–24718.Google ScholarCross Ref
- Scientific Software Development GmbH. 2021. ATLAS.ti. Retrieved June 06, 2021 https://atlasti.com/.Google Scholar
- VERBI GmbH. 2021. MAXQDA. Retrieved June 06, 2021 https://www.maxqda.com/.Google Scholar
- Facebook Inc. 2021. React. Retrieved May 31, 2021 https://reactjs.org/.Google Scholar
- QSR International. 2021. NVivo. Retrieved June 07, 2021 https://www.qsrinternational.com/nvivo-qualitative-data-analysis-software/home.Google Scholar
- Nildo Silva Junior, Larissa Rocha, Luana Almeida Martins, and Ivan Machado. 2020. A survey on test practitioners’ awareness of test smells. In Proceedings of the XXIII Iberoamerican Conference on Software Engineering(CIbSE’ 2020). Curran Associates, Salvador,BA, Brazil, 462–475.Google Scholar
- Leila Karita, Brunna Caroline Mourão, Luana Almeida Martins, Larissa Rocha Soares, and Ivan Machado. 2021. Software industry awareness on sustainable software engineering: a Brazilian perspective. Journal of Software Engineering Research and Development 9 (2021), 15.Google ScholarCross Ref
- Barbara Kitchenham and Shari Lawrence Pfleeger. 2003. Principles of Survey Research Part 6: Data Analysis. SIGSOFT Softw. Eng. Notes 28, 2 (March 2003), 24–27.Google Scholar
- Chakravanti Rajagopalachari Kothari. 2004. Research methodology: Methods and techniques. New Age International, New Delhi, India.Google Scholar
- Sara Mendes Oliveira Lima, Denivan Campos, Larissa Rocha Soares, and Ivan Machado. 2020. Unveiling Practitioners Awareness of Android Apps Regression Testing through an Expert Survey. In Proceedings of the 34th Brazilian Symposium on Software Engineering (Natal, Brazil) (SBES ’20). Association for Computing Machinery, New York, NY, USA, 303–308. https://doi.org/10.1145/3422392.3422470Google ScholarDigital Library
- Jefferson Seide Molléri, Kai Petersen, and Emilia Mendes. 2020. An empirically evaluated checklist for surveys in software engineering. Information and Software Technology 119 (2020), 106240. https://doi.org/10.1016/j.infsof.2019.106240Google ScholarDigital Library
- Finn Nielsen. 2011. A new ANEW: Evaluation of a word list for sentiment analysis in microblogs. CoRR abs/1103.2903 (03 2011).Google Scholar
- The University of Sheffield. 2020. GATE - General Architecture for Text Engineering. Retrieved June 07, 2021 https://gate.ac.uk/.Google Scholar
- Quirkos. 2021. Quirkos. Retrieved June 06, 2021 https://www.quirkos.com/index.html.Google Scholar
- Provalis Research. 2021. Provalis Research. Retrieved June 06, 2021 https://provalisresearch.com/.Google Scholar
- Predictive Analytics Today. 2021. Top 14 qualitative data analysis software. Retrieved June 06, 2021 https://www.predictiveanalyticstoday.com/top-qualitative-data-analysis-software/.Google Scholar
- Tryolabs. 2013. LibreQDA. Retrieved June 07, 2021 https://github.com/tryolabs/libreQDA.Google Scholar
- Stefan Wagner, Daniel Mendez, Michael Felderer, Daniel Graziotin, and Marcos Kalinowski. 2020. Challenges in Survey Research. In Contemporary Empirical Methods in Software Engineering, Michael Feldererand Guilherme Horta Travassos (Eds.). Springer International Publishing, Cham, 93–125.Google Scholar
- Matthew Weinstein. 2020. TAMS. Retrieved June 07, 2021 https://tamsys.sourceforge.io/.Google Scholar
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