Text mining for social science – The state and the future of computational text analysis in sociology

A Systematic Evaluation of Text Mining Methods for Short Texts: Mapping Individuals’ Internal States from Online Posts

“…The RMD was created from the Macquarie Thesaurus (Mohammad and Turney 2013) which includes a rich set of general phrases pertaining to emotions, but lacks words specific to the emotion expression in the informal online context our short texts come from. These results echo the notes of caution that RMDs should only be used when researchers are certain of the similarity of their data to the data the RMD was created and validated on (Macanovic 2022;Wu et al 2018).…”

“…However, when working with previously unmapped concepts or data from a new domain (or type of text), researchers need to create a custom-made dictionary (CMD) from the ground up (Bonikowski and Gidron 2016;Macanovic 2022;Nelson et al 2021;Spörlein and Schlueter 2021). We suggest a simple approach that uses manually coded data to automatically create such dictionaries relying on the concept of word keyness in computational linguistics .…”

“…As such, they tend to lack variables of sociological interest or information about the context in which the texts were generated (Boyd and Schwartz 2021;Macanovic 2022). Some of these challenges can be overcome by combining textual data with other data sourcessuch as survey, census, or experimental data (Boyd and Schwartz 2021;van Loon et al 2020;Salganik 2017).…”

“…Sociological research has, so far, mostly relied on using pre-existing dictionary resources and unsupervised machine learning methods to seek concepts of interest in text (Macanovic 2022) and focused less on methodological decisions and choices (although, see Nelson et al 2021).…”

Câmaras de eco e mis/desinformação sobre vacinas contra a COVID-19 no Twitter: abordagem baseada em machine learning e análise de redes sociais

“…Como o objetivo geral dessa investigação é a análise das redes de interação dos usuários mais expostos à mis/desinformação/controvérsia sobre vacinas no âmbito da pandemia COVID-19, faz-se necessário identificá-la na conversação capturada. Contudo, os dados coletados perfazem quase 24 milhões de tweets, e em razão da inviabilidade de adotar qualquer procedimento manual, fez-se uso de técnicas da Mineração de Textos; uma sub-área da Inteligência Artificial que objetiva extrair informações e padrões em conjuntos de dados textuais (Tao;Hotho;et al, 2005), a qual tem sido empregada, tal qual explicitado por Jung e Lee (2020), em áreas como Educação (Ferreira-Mello et al, 2019), Saúde (Tao;, Ciências Biológicas (Cohen & Hunter, 2008) e Ciências Sociais (Macanovic, 2022).…”