A checklist-based approach to assess the systematicity of the abstracts of reviews self-identifying as systematic reviews
Systematic reviews are crucial for various stakeholders since they allow them to make evidence-based decisions without being overwhelmed by a large volume of research. Systematic reviews are increasingly popular in the software engineering field. The abstract is one of the most important systematic review’s components since it usually reflects the content of the review. It may be the only part of the review that most of the readers will read when needing to form an opinion on a given topic. Besides, the content of an abstract is usually the main information readers use to decide if they want to access the full content of the review or not. Since an abstract usually summarizes a review, readers may therefore mostly rely on that abstract to judge the quality of the review as well as its methodological rigor. However, abstracts are sometimes poorly written and may therefore give a misleading and even harmful picture of the reviews Econtents. To assess abstracts, we propose a measure that allows quantifying the systematicity of reviews Eabstracts i.e., the extent to which these abstracts exhibit good reporting quality. Experiments on 151 reviews published in the software engineering field showed that these reviews Eabstracts exhibit a suboptimal systematicity.
Fri 9 DecDisplayed time zone: Osaka, Sapporo, Tokyo change
09:20 - 10:30 | Review and Natural Language ProcessingTechnical Track / ERA - Early Research Achievements at Room1 Chair(s): Renuka Sindhgatta IBM Research AI | ||
09:20 15mPaper | A checklist-based approach to assess the systematicity of the abstracts of reviews self-identifying as systematic reviews ERA - Early Research Achievements | ||
09:35 15mPaper | Preliminary Analysis of Review Method Selection Based on Bandit Algorithms ERA - Early Research Achievements Takuto Kudo Kindai University, Masateru Tsunoda Kindai University, Amjed Tahir Massey University, Kwabena Ebo Bennin Wageningen University and Research, Akito Monden Okayama University, Koji Toda Fukuoka Institute of Technology, Keitaro Nakasai National Institute of Technology, Kagoshima College, Kenichi Matsumoto Nara Institute of Science and Technology | ||
09:50 20mPaper | Reducing Syntactic Complexity for Information Extraction from Japanese Requirement Specifications Technical Track Maiko Onishi Ochanomizu University, Shinpei Ogata Shinshu University, Kozo Okano Shinshu University, Daisuke Bekki Ochanomizu University | ||
10:10 15mPaper | Quality assurance study with mismatched data in sentiment analysis ERA - Early Research Achievements Tinghui Ouyang National Institute of Advanced Industrial Science and Technology, Yoshiki Seo National Institute of Advanced Industrial Science and Technology, Yutaka Oiwa National Institute of Advanced Industrial Science and Technology |