Narrative as Data: Linguistic and Statistical Tools for the Quantitative Stud...

杨利霞

Narrative as Data: Linguistic and Statistical Tools for the Quantitative Study of Historical Events*

This paper illustrates some linguistic and statistical tools that can be profit
ably used by historians and social historians in the study of events (such as
strikes, demonstrations and other types of collective conflict). More specifi
cally, the paper shows that "semantic grammars" provide rigorous tools for
the collection of rich event narratives. Semantic grammars structure infor
mation around the "canonical form" of the language: noun phrase/verb
phrase, or subject, action, object and their modifiers (e.g. time, space). The
fact that semantic grammars can be easily implemented in a computer
environment using relational database systems (RDBMS) makes feasible the
practical application of such powerful coding schemes. The data that com
puter-based semantic grammars make available are richer, more flexible and
more reliable than those delivered by more traditional content analysis
methods. They are also very well suited for the application of new tools of
data analysis such as network models. Both semantic grammars and network
models are fundamentally concerned with actors and their actions, with
agents and agency. As such, these linguistic and statistical tools should draw
sociology closer to history, traditionally much more concerned with issues
of agency. I illustrate the power of both the linguistic and statistical tools
using data that I collected from some 15,000 newspaper articles on the
1919-1922 period of Italian history, a period characterized by widespread
working-class mobilization (1919—1920, the "red years") and fascist counter
mobilization (1921-1922, the "black years").