The Crowd as a Source of Knowledge - From User Feedback to Fulfilling Requirements

Crowd-based and data-intensive requirements engineering (RE) strategy is considered a promising approach. It enables the gathering and analyzing of information from the general public or the so-called crowd in order to derive validated user requirements. This study aims to conceptualize the process of analyzing information from a crowd to achieve the fulfillment of user requirements. The created model is based on the ADO framework (Antecedents-Decisions-Outcomes). In the empirical part, we chose the Instagram mobile app and user feedback on it as a source of data for the validation of our approach. For extracting antecedents from user feedback, we applied the Latent Dirichlet Allocation (LDA), and then sentiment analysis was performed for each topic to prioritize the most urgent tasks delegated by the crowd.

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Publication Details

Journal
Proceedings of the International Conference on Information Systems Development
Published
2024-09-09
DOI
https://doi.org/10.62036/isd.2024.109
Primary Topic
Open Source Software Innovations
Type
article
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article

The Crowd as a Source of Knowledge - From User Feedback to Fulfilling Requirements

Anna Baj-Rogowska
Proceedings of the International Conference on Information Systems Development
Open Source Software Innovations
article

The Crowd as a Source of Knowledge - From User Feedback to Fulfilling Requirements

Anna Baj-Rogowska
article en

Abstract

Crowd-based and data-intensive requirements engineering (RE) strategy is considered a promising approach. It enables the gathering and analyzing of information from the general public or the so-called crowd in order to derive validated user requirements. This study aims to conceptualize the process of analyzing information from a crowd to achieve the fulfillment of user requirements. The created model is based on the ADO framework (Antecedents-Decisions-Outcomes). In the empirical part, we chose the Instagram mobile app and user feedback on it as a source of data for the validation of our approach. For extracting antecedents from user feedback, we applied the Latent Dirichlet Allocation (LDA), and then sentiment analysis was performed for each topic to prioritize the most urgent tasks delegated by the crowd.

Proceedings of the International Conference on Information Systems Development
Gdańsk University of Technology (PL)
Reduced inequalities
Openalex Percentile: Top 84%
Open Source Software Innovations
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