https://journals-sol.sbc.org.br/index.php/reviews <p style="font-weight: 400;"><strong>SBC Computing Reviews</strong><span style="font-weight: 400;"> — or simply </span><strong>SBC Reviews</strong><span style="font-weight: 400;"> — is a journal published by the Brazilian Computing Society (SBC), dedicated to disseminating comprehensive and rigorous literature reviews across a wide range of Computing research topics. </span></p> <p style="font-weight: 400;"><span style="font-weight: 400;">SBC Reviews appraises submissions of high-quality </span><strong>literature surveys</strong><span style="font-weight: 400;"> that summarize and organize recent research results in a novel way to integrate and add understanding to works in the field, address progress and/or critical assessments relevant to Computing subfields. The journal also welcomes various types of </span><strong>systematic literature reviews</strong><span style="font-weight: 400;"> (SLR) frequently employed in academic research, including multivocal literature reviews (MLR), meta-analyses, and scoping reviews (ScR)/systematic mapping studies (SMS). Updates to existing systematic literature reviews that maintain their currency and relevance are also encouraged. </span></p> <p><span style="font-weight: 400;">We invite authors to submit original literature reviews in either </span><strong>English</strong><span style="font-weight: 400;"> or </span><strong>Portuguese</strong><span style="font-weight: 400;">. Submissions to SBC Reviews should demonstrate methodological rigor in the selection of original studies, with high-quality analyses and clear presentation. Accepted reviews are expected to offer valuable insights by summarizing existing knowledge, identifying research gaps, and guiding future research directions – thereby contributing meaningfully to their respective domains within the Computing subfields. </span></p> Sociedade Brasileira de Computação - SBC en-US SBC Computing Reviews 2966-3938 https://journals-sol.sbc.org.br/index.php/reviews/article/view/6608 <p>The customization of products and services has become an increasing demand in the 21st century; however, it remains underexplored in the educational context. The metaverse emerges as an alternative to enable mass customization in teaching and learning processes, although it requires a systematic analysis of software requirements, particularly non-functional requirements. This study presents the results of a systematic mapping of the literature aimed at identifying and analyzing requirements applied to the development of educational metaverses. Searches were conducted in the ACM Digital Library, IEEE Xplore, Scopus, and Engineering Village databases, resulting in 1,013 identified studies, of which 22 articles published between 2019 and 2024 were selected after the application of inclusion and exclusion criteria. The analysis was structured into four dimensions — Pedagogical, Technical, Social, and Ethical-Legal — defined based on guiding documents and the researchers’ practical experience. The results demonstrate that non-functional requirements play a fundamental role in software quality within immersive educational environments, although they are still insufficiently systematized in this context. Significant gaps were also identified in the social and ethical-legal dimensions, particularly regarding interactivity and security. Furthermore, the findings revealed the limited participation of teachers and students in the structuring of these environments, as well as the tendency of many solutions to merely virtualize existing processes, thereby underutilizing the interaction and customization potential of metaverse technologies. The proposed dimensions contributed to a systematic analysis of requirements, highlighting opportunities for advancing Requirements Engineering in immersive educational solutions and supporting the future development of a taxonomy for educational metaverses.</p> Ricardo Normando Ferreira de Paula Paulo Henrique Mendes Maia Heitor Barros Chrisóstomo Copyright (c) 2026 Ricardo Normando Ferreira de Paula, Paulo Henrique Mendes Maia, Heitor Barros Chrisóstomo https://creativecommons.org/licenses/by/4.0 2026-06-23 2026-06-23 5 1 01 17 10.5753/reviews.2026.6608 https://journals-sol.sbc.org.br/index.php/reviews/article/view/7328 <p>The increasing use of digital data in electoral prediction has motivated a growing body of computational research, yet the field remains methodologically diverse and lacks consolidated comparative frameworks. This article presents a systematic review of computational approaches for electoral outcome prediction using digital data between 2020 and 2025. Following rigorous systematic methodology, searches were conducted across three scientific databases, resulting in 80 primary studies analyzed after applying explicit quality criteria. The review proposes a taxonomy classifying studies by data integration and predictive complexity, enabling systematic identification of methodological patterns. Results reveal geographic concentration in few countries, with Twitter as the dominant platform and sentiment analysis as the most frequent technique. Vote percentage prediction and winner identification represent the primary objectives, evaluated mainly through regression and classification metrics. The field demonstrates numerical expansion with modest geographic diversification, yet persistent challenges remain regarding sample representativeness, cross-context generalization, and absence of standardized validation protocols. Findings indicate the need for broader geographic coverage, reduced platform dependency, and establishment of uniform evaluation criteria to advance methodological maturity in computational electoral prediction.</p> William Takahiro Maruyama Luciano Antonio Digiampietri Copyright (c) 2026 William Takahiro Maruyama, Luciano Antonio Digiampietri https://creativecommons.org/licenses/by/4.0 2026-07-03 2026-07-03 5 1 18 39 10.5753/reviews.2026.7328