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21
Assessing the use of back translation: the shortcomings of back translation as a quality testing method
In: International Journal of Social Research Methodology ; 20 ; 6 ; 573-584 (2021)
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22
Integrating Manual and Automatic Annotation for the Creation of Discourse Network Data Sets
In: Politics and Governance ; 8 ; 2 ; 326-339 ; Policy Debates and Discourse Network Analysis (2021)
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23
Measurement Invariance Across Immigrant and Non-Immigrant Populations on PISA Cognitive and Non-Cognitive Scales
In: Doctoral Dissertations (2021)
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24
Comparing textual genres in Spanish: the case of the tourism domain
In: Ibérica, Iss 42, Pp 163-190 (2021) (2021)
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25
Approches quantitatives de l'analyse des prédictions en traduction automatique neuronale (TAN)
In: JADT 2020 : 15èmes Journées Internationales d'Analyse statistique des Données Textuelles ; https://hal.archives-ouvertes.fr/hal-03049589 ; JADT 2020 : 15èmes Journées Internationales d'Analyse statistique des Données Textuelles, Université de Toulouse, Jun 2020, Toulouse, France ; https://jadt2020.sciencesconf.org (2020)
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26
La textométrie en question
In: ISSN: 0015-9409 ; Le Français Moderne - Revue de linguistique Française ; https://halshs.archives-ouvertes.fr/halshs-02902088 ; Le Français Moderne - Revue de linguistique Française, CILF (conseil international de la langue française), 2020, Linguistique et traitements quantitatifs, 88 (1), pp.26-43 ; http://www.le-francais-moderne.com/ (2020)
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27
Применение фильтра Калмана для навигационных задач железнодорожного транспорта ... : выпускная квалификационная работа бакалавра ...
Хатымов, Ренат. - : Санкт-Петербургский политехнический университет Петра Великого, 2020
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28
Doing Linguistics with a Corpus: Methodological Considerations for the Everyday User. Jesse Egbert, Tove Larsson, Douglas Biber ...
Mattei, Elena. - : Iperstoria, 2020
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29
Economic and mathematical modeling of risks of introduction of information and communication technologies ...
KOLODIYCHUK, A.V.. - : Zenodo, 2020
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30
Economic and mathematical modeling of risks of introduction of information and communication technologies ...
KOLODIYCHUK, A.V.. - : Zenodo, 2020
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31
Statistical Complexity Analysis of Turing Machine tapes with Fixed Algorithmic Complexity Using the Best-Order Markov Model
In: Entropy ; Volume 22 ; Issue 1 (2020)
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32
Analyzing Given Names ... : Exploring Potentials for a Personalized Name Discovery on Nameling.net ...
Müller, Jürgen. - : Universität Kassel, 2020
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33
THE PROBLEM OF GENERAL UNDERDEVELOPMENT OF SPEECH IN CHILDREN OF PRESCHOOL AGE ...
Tasmuratova, B.T.; Omarova, A.S.. - : Инфинити, 2020
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34
Opinion-Mining on Marglish and Devanagari Comments of YouTube Cookery Channels Using Parametric and Non-Parametric Learning Models
In: Big Data and Cognitive Computing ; Volume 4 ; Issue 1 (2020)
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35
Development of Gaussian Learning Algorithms for Early Detection of Alzheimer's Disease
In: FIU Electronic Theses and Dissertations (2020)
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36
The Quality of Big Data: Development, Problems, and Possibilities of Use of Process-Generated Data in the Digital Age
In: Historical Social Research ; 45 ; 3 ; 209-243 (2020)
Abstract: The paper introduces the HSR Forum on digital data by discussing what big data are. The authors show that big data are not a new type of social science data but actually one of the oldest forms of social science data. In addition, big data are not necessarily digital data. Regardless, current methodological debates often assume that “big data” are “digital data.” The authors thus also show that digital data have a big drawback concerning data quality because they do not cover the whole population – due to so-called digital divides, not everybody is on the internet, and who is on the internet, is socially structured. The result is a selection bias. Based on this analysis, the paper concludes that big data and digital data are data like any other type of data – they have both advantages and specific blind spots. So rather than glorifying or demonising them, it seems much more sensible to discuss which specific advantages and drawbacks they have as well as when and how they are better suited for answering specific research questions and when and how other types of data are better suited – these are the questions that are addressed in this HSR Forum.
Keyword: 10200; 30300; anthropology; big data; computational social sciences; Computer Methods; corpus linguistics; data capture; data quality; Datengewinnung; Datenqualität; digital data; digital divide; digital methods; Digitale Spaltung; Digitalisierung; digitalization; empirical social research; empirische Sozialforschung; Erhebungstechniken und Analysetechniken der Sozialwissenschaften; historical development; historical social research; historical sociology; historische Entwicklung; historische Sozialforschung; Internet; mass data; Methodologie; methodology; Methods and Techniques of Data Collection and Data Analysis; process-generated data; process-produced data; social research; social science methodology; Social sciences; social structure; sociology; Sozialstruktur; Sozialwissenschaften; Soziologie; Statistical Methods; survey methodology
URL: https://doi.org/10.12759/hsr.45.2020.3.209-243
https://www.ssoar.info/ssoar/handle/document/68224
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37
Adults' Identity in Acculturation Settings: The Multigroup Ethnic & National Identity Measure (MENI)
In: Identity: An International Journal of Theory and Research ; 19 ; 4 ; 245-257 (2020)
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38
A rationale for unanimity in committees
In: SP II 2017-308 ; Discussion Papers / Wissenschaftszentrum Berlin für Sozialforschung, Forschungsschwerpunkt Markt und Entscheidung, Abteilung Ökonomik des Wandels ; 41 (2020)
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39
An English-language adaptation of the Interpersonal Trust Short Scale (KUSIV3)
In: Measurement Instruments for the Social Sciences ; 1-12 (2020)
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40
Adjusting for treatment switching in oncology trials: a systematic review and rRecommendations for reporting
Sullivan, T.; Latimer, N.; Gray, J.. - : Elsevier, 2020
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