Editing Social network analysis (section)

=== Textual analysis applications ===
Large textual corpora can be turned into networks and then analyzed using social network analysis. In these networks, the nodes are Social Actors, and the links are Actions. The extraction of these networks can be automated by using parsers. The resulting networks, which can contain thousands of nodes, are then analyzed using tools from network theory to identify the key actors, the key communities or parties, and general properties such as the robustness or structural stability of the overall network or the centrality of certain nodes.<ref>{{cite journal |last1=Sudhahar |first1=Saatviga |last2=De Fazio |first2=Gianluca |last3=Franzosi |first3=Roberto |last4=Cristianini |first4=Nello |title=Network analysis of narrative content in large corpora |journal=Natural Language Engineering |date=January 2015 |volume=21 |issue=1 |pages=81–112 |doi=10.1017/S1351324913000247 |hdl=1983/dfb87140-42e2-486a-91d5-55f9007042df |s2cid=3385681 |url=https://research-information.bris.ac.uk/en/publications/dfb87140-42e2-486a-91d5-55f9007042df |hdl-access=free }}</ref> This automates the approach introduced by Quantitative Narrative Analysis,<ref>Quantitative Narrative Analysis; Roberto Franzosi; Emory University © 2010</ref> whereby subject-verb-object triplets are identified with pairs of actors linked by an action, or pairs formed by actor-object.<ref name="ReferenceA" />
[[File:Tripletsnew2012.png|thumb|right|Narrative network of US Elections 2012<ref name="ReferenceA">{{cite journal |last1=Sudhahar |first1=Saatviga |last2=Veltri |first2=Giuseppe A |last3=Cristianini |first3=Nello |title=Automated analysis of the US presidential elections using Big Data and network analysis |journal=Big Data & Society |date=May 2015 |volume=2 |issue=1 |doi=10.1177/2053951715572916 |doi-access=free |hdl=2381/31767 |hdl-access=free }}</ref>]]
In other approaches, textual analysis is carried out considering the network of words co-occurring in a text. In these networks, nodes are words and links among them are weighted based on their frequency of co-occurrence (within a specific maximum range).