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Updated methods list authored by Gallenkamp, Fabian's avatar Gallenkamp, Fabian
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......@@ -111,11 +111,11 @@ Extract relationships between entities.
Retrieve relevant informations in response to the information requests.
=== indexing
==== indexing
'organize data in such a way that it can be easily retrieved later on'(<<Ignatow_etal2017>>,137)
=== searching/querying
==== searching/querying
'take information requests in the form of queries and return relevant documents'(<<Ignatow_etal2017>>,137). There are different models in order to estimate the similarity between records and the search queries (e.g. boolean, vector space or a probabilistic model)(ibid).
......@@ -169,7 +169,7 @@ Inclusion of meta-data. Refer especially <<roberts2013>>.
===== automated narrative, argumentative structures, irony, metaphor detection/extraction
For automated narrative methapor analysis see (<<Ignatow_etal2017>>, 89-106. For argumentative structures(Task: Retrieving sentential arguments for any given controversial topic) <<Stab_etal2018>> .Refer for a current overview <<Cabrio2018>>.
==== network analysis/modelling
......@@ -260,10 +260,6 @@ Guide open-answer questions with user feedback.
===
== social complexity modeling/ social simulation
......@@ -275,6 +271,8 @@ Using methods to predict the future for estimation of current values. (Example:
[bibliography]
== References
- [[[Cabrio2018]]] Cabrio, E., & Villata, S. (2018). Five years of argument mining: a data-driven analysis. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (pp. 5427–5433).
- [[[Han_etal2012]]] Han, J., Kamber, M., & Pei, J. (2012). Data Mining: Concepts and Techniques. Saint Louis, UNITED STATES: Elsevier Science & Technology.
- [[[Ignatow_etal2017]]] Ignatow, G., & Mihalcea, R. F. (2017). Text mining: A guidebook for the social sciences. Los Angeles, London, New Delhi, Singapore, Washington DC, Melbourne: Sage.
......@@ -291,4 +289,6 @@ Using methods to predict the future for estimation of current values. (Example:
- [[[Salganik2018]]] Salganik, M. J. (2018). Bit by bit: Social research in the digital age.
- [[[Stab_etal2018]]] Stab, C., Daxenberger, J., Stahlhut, C., Miller, T., Schiller, B., Tauchmann, C., . . . Gurevych, I. (2018). ArgumenText: Searching for Arguments in Heterogeneous Sources. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations (pp. 21–25).
- [[[Wickham_etal2017]]] Wickham, H., & Grolemund, G. (2017). R for Data Science: Import, tidy, transform, visualize, and model data. Beijing, Boston, Farnham, Sebastopol, Tokyo: O’Reilly UK Ltd.