scholarly journals The growing field of interdisciplinary research on user comments: A computational scoping review

2021 ◽  
pp. 146144482199449
Author(s):  
Max Schindler ◽  
Emese Domahidi
Keyword(s):  
Scoping Review ◽  
Text Analysis ◽  
Qualitative Evaluation ◽  
Audience Participation ◽  
Current State ◽  
User Comments ◽  
Important Field ◽  
Automatic Text Analysis ◽  
Structural Topic Modeling ◽  
Automatic Text

Online user comments (UCs) as the most popular type of online audience participation nowadays form a popular and important field of research. The widespread examination of UCs across different disciplines leads to a variety of terms and constructs and thus a missing clarity about the discussed topics. With this computational scoping review, we uncovered six relevant, overarching topics and their development in the field. Due to the combination of an automatic text analysis via structural topic modeling and a qualitative evaluation, we were able to describe the current state of UC research and found an inherently interdisciplinary body of literature. We observed an inter- and intradisciplinary fragmentation and call for a systematization of the used terms, constructs, and examined topics.

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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