We identify three gaps that limit the utility and obstruct the progress of computational text
analysis methods (CTAM) for social science research. First, we contend that CTAM …

The emergence of big data and computational tools has introduced new possibilities for
using large-scale textual sources in sociological research. Recent work in sociology of …

The empirical identification of frames drawing on automated text analysis has been
discussed intensely with regard to the validity of measurements. Adding to an evolving …

This paper examines how the COVID-19 pandemic associates with Twitch users' emotion,
using natural language processing (NLP) as a method. Two comparable sets of text data …

The goal of this paper is to evaluate two methods for the topic modeling of multilingual
document collections:(1) machine translation (MT), and (2) the coding of semantic concepts …

Research in the area of human information interaction (HII) typically represents viewpoints
on debated topics in a binary fashion, as either against or in favor of a given topic (eg, the …

Social media is a popular source of nutrition information and can influence food choice.
Instagram is widely used in Australia, and nutrition is frequently discussed on Instagram …

Scholars have access to a rich source of political discourse via social media. Although
computational approaches to understand this communication are being used, they tend to …

Communication research frequently applies computational text analysis methods (CTAM) to
detect and measure social science constructs. However, the validity of these measures can …

Dictionary-based approaches to computational text analysis have been shown to perform
relatively poorly, particularly when the dictionaries rely on simple bags of words, are not …