Search results for "datatiede"
showing 5 items of 5 documents
The Datafication of Hate: Expectations and Challenges in Automated Hate Speech Monitoring.
2020
Laaksonen, S-M.; Haapoja, J.; Kinnunen, T., Nelimarkka, M. & Pöyhtäri, R. (2020, accepted). . Frontiers in Big Data: Data Mining and Management / Critical Data and Algorithm Studies. doi:10.3389/fdata.2020.00003 Hate speech has been identified as a pressing problem in society and several automated approaches have been designed to detect and prevent it. This paper reports and reflects upon an action research setting consisting of multi-organizational collaboration conducted during Finnish municipal elections in 2017, wherein a technical infrastructure was designed to automatically monitor candidates' social media updates for hate speech. The setting allowed us to engage in a 2-fold investiga…
Multiobjective optimization and decision making in engineering sciences
2021
AbstractReal-world decision making problems in various fields including engineering sciences are becoming ever more challenging to address. The consideration of various competing criteria related to, for example, business, technical, workforce, safety and environmental aspects increases the complexity of decision making and leads to problems that feature multiple competing criteria. A key challenge in such problems is the identification of the most preferred trade-off solution(s) with respect to the competing criteria. Therefore, the effective combination of data, skills, and advanced engineering and management technologies is becoming a key asset to a company urging the need to rethink how…
Expectations for supporting student engagement with learning analytics : an academic path perspective
2021
There has been a growing interest in higher education to explore how learning analytics (LA) could be used to support student engagement. Providing actionable feedback with LA for students is an emerging area of research. Previous studies have commonly focused on course-level aspects of supporting engagement with LA, but students' perspectives have received limited attention. This study analyzed pre-service teachers’ needs and expectations for LA to support student engagement on the academic path level, which means observing the continuum of study periods and academic years. Qualitative content analysis was conducted for video-recorded student small-group conversations to analyze in-depth h…
Haavoittuvuuden kudelmat : digitaalinen subjekti ja haavoittuvuus datavetoista yhteiskuntaa käsittelevässä tutkimuskirjallisuudessa
2021
Artikkelissa tarkastellaan sitä, millaisia merkityksiä haavoittuvuudelle on annettu datavetoista yhteiskuntaa ja digitaalista subjektia koskevassa tutkimuskirjallisuudessa. Artikkeli perustuu kirjallisuuskatsaukseen, joka on tehty vuosina 2015–2020 ilmestyneistä haavoittuvuutta datafikaation kontekstissa käsittelevistä tieteellisistä julkaisuista. Kirjallisuushaut tehtiin yhteiskuntatieteiden alojen keskeisistä tietokannoista ja digitaalisista kirjastoista. Hakujen pohjalta tutkimuskirjallisuus järjestettiin neljään teemakokonaisuuteen: 1) datavalvonnan tuottamat haavoittuvuudet, 2) data tietämisen tapana ja osallisuutena, 3) digitaalisten subjektien kategorisointi ja näkyvyyden säätely sek…
Data-Driven Evolutionary Optimization: An Overview and Case Studies
2019
Most evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward. In solving many real-world optimization problems, however, such objective functions may not exist, instead computationally expensive numerical simulations or costly physical experiments must be performed for fitness evaluations. In more extreme cases, only historical data are available for performing optimization and no new data can be generated during optimization. Solving evolutionary optimization problems driven by data collected in simulations, physical experiments, production processes, or daily life are termed data-driven evolutionary optimization. In this…