scholarly journals Psychometric evaluation of the Serbian dictionary for automatic text analysis - LIWCser

Psihologija ◽  
2014 ◽  
Vol 47 (1) ◽  
pp. 5-32 ◽  
Author(s):  
Jovana Bjekic ◽  
Ljiljana Lazarevic ◽  
Marko Zivanovic ◽  
Goran Knezevic
Keyword(s):  
Text Analysis ◽  
Psychometric Evaluation ◽  
Scientific Paper ◽  
Personality Psychology ◽  
World Languages ◽  
Word Level ◽  
Different Types ◽  
Linguistic Inquiry ◽  
Automatic Text Analysis ◽  
Automatic Text

LIWC (Linguistic Inquiry and Word Count) is widely used word-level content analysis software. It was used in large number of studies in the fields of clinical, social and personality psychology, and it is adapted for text analysis in 11 world languages. The aim of this research was to validate empirically newly constructed adaptation of LIWC software for Serbian language (LIWCser). The sample of the texts consisted of 384 texts in Serbian and 141 texts in English. It included scientific paper abstracts, newspaper articles, movie subtitles, short stories and essays. Comparative analysis of Serbian and English version of the software demonstrated acceptable level of equivalence (ICCM=.70). Average coverage of the texts with LIWCser dictionary was 69.93%, and variability of this measure in different types of texts is in line with expected. Adaptation of LIWC software for Serbian opens entirely new possibilities of assessment of spontaneous verbal behaviour that is highly relevant for different fields of psychology.

Proactive screening for depression through metaphorical and automatic text analysis

2012 ◽  
Vol 56 (1) ◽  
pp. 19-25 ◽  
Author(s):  
Yair Neuman ◽  
Yohai Cohen ◽  
Dan Assaf ◽  
Gabbi Kedma
Keyword(s):  
Text Analysis ◽  
Automatic Text Analysis ◽  
Automatic Text

Studying Political Decision Making With Automatic Text Analysis

2019 ◽  
Author(s):  
Wouter van Atteveldt ◽  
Kasper Welbers ◽  
Mariken van der Velden
Keyword(s):  
Political Science ◽  
Text Analysis ◽  
Political Ideology ◽  
Numerical Representation ◽  
Political Decision ◽  
Text Collections ◽  
Textual Data ◽  
Automatic Text Analysis ◽  
Political Decision Making ◽  
Automatic Text

Analyzing political text can answer many pressing questions in political science, from understanding political ideology to mapping the effects of censorship in authoritarian states. This makes the study of political text and speech an important part of the political science methodological toolbox. The confluence of increasing availability of large digital text collections, plentiful computational power, and methodological innovations has led to many researchers adopting techniques of automatic text analysis for coding and analyzing textual data. In what is sometimes termed the “text as data” approach, texts are converted to a numerical representation, and various techniques such as dictionary analysis, automatic scaling, topic modeling, and machine learning are used to find patterns in and test hypotheses on these data. These methods all make certain assumptions and need to be validated to assess their fitness for any particular task and domain.

Automatic Text Analysis

Science ◽  
1970 ◽  
Vol 168 (3929) ◽  
pp. 335-343 ◽  
Author(s):  
G. Salton
Keyword(s):  
Text Analysis ◽  
Automatic Text Analysis ◽  
Automatic Text
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