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#computationalSocialScience

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Pollux

Unser FoBi-Bericht zusammen mit @SocioHub_FID ist soeben in der o-bib - Das offene Bibliotheksjournal erschienen: "Forschungsnah und innovativ - Rückblick auf die VDB-Fortbildung für Fachreferent*innen der Soziologie und Politikwissenschaft"
o-bib.de/bib/article/view/6163 #FID #Fachreferat #DOA #OpenAccess #dataliteracy #ComputationalSocialScience

www.o-bib.deForschungsnah und innovativ: Rückblick auf die VDB-Fortbildung für Fachreferent*innen der Soziologie und Politikwissenschaft | o-bib. Das offene Bibliotheksjournal / Herausgeber VDB
Johannes Breuer

For our new project "Fostering Proactive Replicability in Computational Communication Science via Frontloading Effort and Automating Protocols" within the DFG priority program META-REP, @drfollowmario and I are looking for a Ph.D. student: rrr.is/repccs2job
Application deadline: Dec 6, 2024
Project start: March 1, 2025
#commodon
@communicationscholars
#computationalsocialscience

www.hidden-professionals.deWissenschaftliche*n Mitarbeiter*in (Doktorand*in) GESIS – Leibniz-Institut für Sozialwissenschaften ist eine von Bund und Ländern finanzierte, international tätige sozialwissenschaftliche Einrichtung der Leibniz-Gemeinschaft.Wir suchen zum 01.03.2025 für den Standort Köln in der Abteilung Computational Social Science (CSS), Team Digital Society Observatory für das Projekt „Fostering Proactive Replicability in Computational Communication Science via Frontloading Effort and Automating Protocols“ (AutoFrontCCS) eine*n
Johannes Breuer

New open-access publication by Philipp Knöpfle, @drfollowmario, and me in Publizistik: "Key topic or bare necessity? How Research Ethics are Addressed and Discussed in Computational Communication Science" link.springer.com/article/10.1
#computationalsocialscience #commodon @communicationscholars

SpringerLinkKey topic or bare necessity? How Research Ethics are Addressed and Discussed in Computational Communication Science - PublizistikIn Computational Communication Science (CCS) researchers grapple with intricate ethical challenges arising from the collection and analysis of complex data sets, often including sensitive or copyrighted data. Taking into consideration differences between the two main lines of philosophical reasoning in the realm of (research) ethics—deontology and consequentialism—we argue that ethical challenges faced in CCS are multidimensional and, hence, require multiple perspectives and approaches. Our general considerations are complemented by an empirical study that aims to assess the nature, prevalence, and discussion of ethical issues in CCS literature. Through a manual content analysis of 476 CCS publications, we shed light on ethical challenges as well as reflections thereof by CCS researchers. Notably, we find that only 5.88% of studies explicitly address general ethical considerations. Ethical review processes are also only mentioned in 6.51% of the considered studies, with the majority focusing on specific ethical procedures, such as obtaining informed consent, data anonymization measures, or debriefing. This suggests that, in the absence of consensus and field-specific standards, researchers in CCS prioritize context-specific ethical procedures, emphasizing the importance of flexibility in addressing ethical considerations.
alissonmasoares

For those interested in Topic Modeling and #textanalysis #textmining, this free article discusses some forms of validating the results.

"Topic Model Validation Methods and their Impact
on Model Selection and Evaluation". COMPUTATIONAL COMMUNICATION RESEARCH 5.1 (2023) 1–26

#ComputationalSocialScience

aup-online.com/content/journal

www.aup-online.comTopic Model Validation Methods and their Impact on Model Selection and Evaluation | Amsterdam University Press Journals OnlineTopic Modeling is currently one of the most widely employed unsupervised text-as-data techniques in the field of communication science. While researchers increasingly recognize the importance of validating topic models and given the prevalence of discussions of inadequate validation practices in the literature, there is limited understanding of the consequences of employing different validation strategies when evaluating topic models. This study applies two different methods for topic modeling to the same text corpus. It uses four validation strategies to assess how the choice of validation method affects the final model selection and evaluation. Our findings indicate that different approaches and methods lead to different model choices and evaluations, which is problematic. This might lead to unwanted results in case the choice of model has a decisive impact on findings and, consequently, on theory development and practical implications.
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