Search results for "tekstinlouhinta"
showing 10 items of 16 documents
Automatic Profiling of Open-Ended Survey Data on Medical Workplace Teaching
2019
On-the-job medical training is known to be challenging due to the fast-paced environment and strong vocational profile. It relies on on-site supervisors, mainly doctors and nurses with long practical experience, who coach and teach their less experienced colleagues, such as residents and healthcare students. These supervisors receive pedagogical training to ensure that their guidance and teaching skills are constantly improved. The aim of such training is to develop participants’ patient, collegiate and student guidance skills in a multiprofessional environment, and to expand their understanding of guidance as part of their work as supervisors of healthcare professionals. In this paper, we …
Extracting locations from sport and exercise-related social media messages using a neural network-based bilingual toponym recognition model
2022
Funding: This study is a part of the “Equality in suburban physical activity environments, YLLI” research project (in Finnish: Yhdenvertainen liikunnallinen lähiö, YLLI). The project is being financed by the research program about suburban in Finland “Lähiöohjelma 2020-2022” coordinated by the Ministry of Environment (grant recipient: Dr. Petteri Muukkonen). Sport and exercise contribute to health and well-being in cities. While previous research has mainly focused on activities at specific locations such as sport facilities, “informal sport” that occur at arbitrary locations across the city have been largely neglected. Such activities are more challenging to observe, but this challenge may…
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…
Establishing Video Game Genres Using Data-Driven Modeling and Product Databases
2015
Establishing genres is the first step toward analyzing games and how the genre landscape evolves over the years. We use data-driven modeling that distils genres from textual descriptions of a large collection of games. We analyze the evolution of game genres from 1979 till 2010. Our results indicate that until 1990, there have been many genres competing for dominance, but thereafter sport-racing, strategy, and action have become the most prevalent genres. Moreover, we find that games vary to a great extent as to whether they belong mostly to one genre or to a combination of several genres. We also compare the results of our data-driven model with two product databases, Metacritic and Mobyga…
A First Experiment on Including Text Literals in KGloVe
2018
Graph embedding models produce embedding vectors for entities and relations in Knowledge Graphs, often without taking literal properties into account. We show an initial idea based on the combination of global graph structure with additional information provided by textual information in properties. Our initial experiment shows that this approach might be useful, but does not clearly outperform earlier approaches when evaluated on machine learning tasks.
Reconsidering authorship in the Ciceronian corpus through computational authorship attribution
2019
In recent years, methods of computational authorship attribution have offered promising results for the reattribution of classical texts. We use and further develop these methods to verify the authorship of several texts belonging or related to the Ciceronian corpus: Rhetorica ad C. Herennium, De inventione, De optimo genere oratorum, and Commentariolum petitionis. We use two classifiers, Support Vector Machine and Convolutional Neural Network, of which the latter is more accurate except in regard to certain aspects of vocabulary. The most important of our results is that Commentariolum petitionis seems to be authored by Marcus Cicero, not by his brother Quintus. Negli ultimi anni metodi co…
Evolving Conceptualisations of Internationalism in the UK Parliament : Collocation Analyses from the League to Brexit
2020
This chapter explores a historical distant reading strategy of British Parliamentary discourse. It uses historical collocation analyses of ‘internationalism’ and the ‘international’ in the British Hansard Corpus and a selection of Commons and Lords debates concerning British membership in international organisations as it relates to the League of Nations, United Nations, Council of Europe, EEC and Brexit. The collocates that were deemed to be politically significant are grouped in 13 loose semantic fields. This macro-level analysis of long-term trends of discourse is supplemented with an analysis of the said key debates in their historical contexts, including comparisons between the two Hou…
Explaining information technology users’ ways of mitigating technostress
2017
Technostress refers to the inability of an individual to deal with information technology (IT) in a healthy manner. Researchers, practitioners, and medical professionals have emphasized the omnipresence of technostress and its severe outcomes, including poor well-being and burnout. Despite the importance of the phenomenon, prior research has paid limited attention to how technostress can be mitigated. The few existing studies examine organizational mitigation mechanisms, but we could not find any studies that focus on individual IT users’ own ways of mitigating technostress outside of work. To address the research gap, we conducted a qualitative study to uncover users’ ways of mitigating te…
The Effect of Textual Producer-Generated Descriptions on Demand of Mobile Applications
2017
We analyze the impact of different app description characteristics on app demand on the basis of panel data for six months and 1081 distinct apps. We use several text mining techniques in order to operationalize the descriptions’ textual characteristics. The extracted variables are then used in an econometric investigation to examine their impact on apps’ downloads. Our results provide evidence that app descriptions have an effect on demand. Apps with upfront price should be described in a neutral tone. Apps without an upfront price but with in-app purchase option should be offered with rather short descriptions that are written in a formal and subjective style. peerReviewed
Automatic content analysis in collaborative inquiry-based learning
2019
In the field of science education, content analysis is a popular way to analyse collaborative inquiry-based learning (CIBL) processes. However, content analysis is time-consuming when conducted by humans. In this paper, we introduce an automatic content analysis method to identify the different inquiry-based learning (IBL) phases from authentic student face-to-face discussions. We illustrate the potential of automatic content analysis by comparing the results of manual content analysis (conducted by humans) and automatic content analysis (conducted by computers). Both the manual and automatic content analyses were based on manual transcriptions of 11 groups’ CIBL processes. Two researchers …