Semi-supervised Textual Analysis and Historical Research Helping Each Other: Some Thoughts and Observations.
Future historians will describe the rise of the World Wide Web as the turning point of their academic profession. As a matter of fact, thanks to an unprecedented amount of digitization projects and to the preservation of born-digital sources, for the first time they have at their disposal a gigantic...
| Publicado en: | International Journal of Humanities & Arts Computing: A Journal of Digital Humanities Vol. 10; no. 1; pp. 63 - 78 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Edinburgh University Press
Mar2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=113576267&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 113576267 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 17538548 2QD7 jtl: International Journal of Humanities & Arts Computing: A Journal of Digital Humanities issn: 17538548 maglogo: N pubinfo: dt: Mar2016 vid: 10 iid: 1 pid: 2327 pub: Edinburgh University Press artinfo: ui: 113576267 10.3366/ijhac.2016.0160 ppf: 63 ppct: 15 formats: fmt: @attributes: type: P size: 123KB tig: atl: Semi-supervised Textual Analysis and Historical Research Helping Each Other: Some Thoughts and Observations. aug: au: Nanni, Federico Kümper, Hiram Ponzetto, Simone Paolo su: Archives Data analysis History Digital libraries Content analysis sug: subj: Archives Data analysis History Digital libraries Content analysis keyword: born-digital archives data analysis historical studies semi-supervised methods ab: Future historians will describe the rise of the World Wide Web as the turning point of their academic profession. As a matter of fact, thanks to an unprecedented amount of digitization projects and to the preservation of born-digital sources, for the first time they have at their disposal a gigantic collection of traces of our past. However, to understand trends and obtain useful insights from these very large amounts of data, historians will need more and more fine-grained techniques. This will be especially true if their objective will turn to hypothesis-testing studies, in order to build arguments by employing their deep in-domain expertise. For this reason, we focus our paper on a set of computational techniques, namely semi-supervised computational methods, which could potentially provide us with a methodological turning point for this change. As a matter of fact these approaches, due to their potential of affirming themselves as both knowledge and data driven at the same time, could become a solid alternative to some of the today most employed unsupervised techniques. However, historians who intend to employ them as evidences for supporting a claim, have to use computational methods not anymore as black boxes but as a series of well known methodological approaches. For this reason, we believe that if developing computational skills will be important for them, a solid background knowledge on the most important data analysis and results evaluation procedures will become far more capital. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of International Journal of Humanities & Arts Computing: A Journal of Digital Humanities is the property of Edinburgh University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: International Journal of Humanities & Arts Computing: A Journal of Digital Humanities holder: Edinburgh University Press dt: @attributes: year: 2016 holdings: @attributes: islocal: N |
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