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@phdthesis{Sørhaug2022,

title = {På sporet av aktørar som skriv Ein studie av to digitale samskrivingskasus i ein ungdomsskoleklasse},

author = {Jon Olav Sørhaug},

editor = {Universitetet i Agder},

url = {https://uia.brage.unit.no/uia-xmlui/bitstream/handle/11250/3035826/Dissertation.pdf?sequence=4},

year  = {2022},

date = {2022-06-05},

urldate = {2022-06-05},

abstract = {On the Trail of Actors Who Write is a study of two digital cases of collaborative writing in a Norwegian lower secondary school class. The study maps, analyzes and discusses the writing process in two collaborative writing groups, consisting of six students – in close collaboration with software, texts from the Internet and other digital actors, during three double lessons in February 2020.

The study applies socio-material theory to writing in school contexts. The conceptual framework is based on actor-network theory (ANT), theories of linguistic materiality, visual network analysis (VNA) and case study methodology. The collected material in the study consists of both quantitative and qualitative data: student texts and source texts, video and screen recordings, and also interviews with the teacher and students participating in the project.

Central to the study is the question of how human and digital actors interact while writing, and which role technology plays in this process. The study reveals that the student texts are produced through a number of negotiations and trials of strength between students, search engines, digital source texts and writing software. Search engines greatly influence the planning processes in that they select, prioritize and promote other actors' texts, and indeed specific parts of these texts. The source texts affect the composition of student texts by circulating, replicating and, in some cases, mutating the linguistic material into

their texts. Writing software affects students' spelling through writing suggestions and corrective interruptions in the digital environment. The production of the student texts can thus be seen as transformations of linguistic material originating in the digital actors that participate in the writing process, and to some extent originating in the students themselves.

In several of the situations observed in these two collaborative writing cases, it is the digital actors that seem to have the greatest power of negotiation and impact. A practical implication for writing education can therefore be to strengthen lower secondary school students' critical approach and ability to negotiate with digital actors, so that students can make more independent choices while writing, also when collaboratively writing with each other and through digital technology.},

keywords = {},

pubstate = {published},

tppubtype = {phdthesis}

}

@phdthesis{Ruiz2017,

title = {Concept-based and relation-based corpus navigation : applications of natural language processing in digital humanities},

author = {Pablo Ruiz},

url = {https://tel.archives-ouvertes.fr/tel-01575167v2},

year  = {2017},

date = {2017-06-23},

school = {PSL Research University},

abstract = {Social sciences and Humanities research is often based on large textual corpora, that it would be unfeasible to read in detail.  Natural Language Processing (NLP) can identify important concepts and actors mentioned in a corpus, as well as the relations between them. Such information can provide an overview of the corpus useful for domain-experts, and help identify corpus areas relevant for a given research question. To automatically annotate corpora relevant for Digital Humanities (DH), the NLP technologies we  applied  are, first, Entity Linking, to identify corpus actors and concepts. Second, the relations between actors and concepts were determined based on an NLP pipeline which provides semantic role labeling and syntactic dependencies among other information. Part I outlines the state of the art, paying attention to how the technologies have been applied in DH. Generic NLP tools were used. As the efficacy of NLP methods depends on the corpus, some technological development was undertaken, described in Part II, in order to better adapt to the corpora in our case studies. Part II also shows an intrinsic evaluation of the technology developed, with satisfactory results. The technologies were applied to three very different corpora, as described in Part III. First, the manuscripts of Jeremy Bentham. This is a 18th–19th century corpus in political philosophy. Second, the Poli Informatics corpus, with heterogeneous materials about the American financial crisis of 2007–2008. Finally, the Earth Negotiations Bulletin (ENB), which covers international climate summits since 1995, where treaties like the Kyoto Protocol or the Paris Agreements get negotiated. For each corpus, navigation interfaces were developed. These user interfaces (UI) combine networks, full-text search and structured search based on NLP annotations. As an example, in the ENB corpus interface, which covers climate policy negotiations, searches can be performed based on relational information identified in the corpus: The negotiation actors having discussed a given issue using verbs indicating supportor opposition can be searched, as well as all statements where a given actor has expressed support or opposition. Relation information is employed, beyond simple co-occurrence between corpus terms. The UIs were evaluated qualitatively with domain-experts, to assess their potential usefulness for research in the experts’ domains. First, we payed attention to whether the corpus representations we created correspond to  experts’ knowledge of thecorpus, as an indication of the sanity of the outputs we produced. Second, we tried to determine whether experts could gain new insight on the corpus by using the applications, e.g. if they found evidence unknown to them or new research ideas. Examples of insight gain were attested with the ENB interface; this constitutes a good validation of the work carried out in the thesis. Overall, the applications’ strengths and weaknesses were pointed out, outlining possible improvements as future work.},

keywords = {},

pubstate = {published},

tppubtype = {phdthesis}

}