A Mixed Methods Study of Public Perception of Social Distancing: Integrating Qualitative and Computational Analyses for Text Data

Ho, Pauline; Chen, Kaiping; Shao, Anqi; Bao, Luye; Ai, Angela; Tarfa, Adati; Brossard, Dominique; Brown, Lou; Bräuer, Markus

doi:10.1177/15586898211020862

Cited by 14 publications

(16 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The research was conducted using relevant mixed methods through a sequential explanatory strategy, as outlined in (Ho et al, 2021;Leavy, 2017). Initially, quantitative descriptive analysis was primarily applied, followed by a qualitative case study to delve deeper into the issues.…”

Section: Methodsmentioning

confidence: 99%

The Importance of Participatory Communication in Development Planning Deliberations for Agritourism Village Enhancement

Sulaiman,

Rosyadi,

Handoko

et al. 2024

JICC

View full text Add to dashboard Cite

Previous research has focused on the implementation of Development Planning Deliberation (DPD) as a tool to improve development communication among stakeholders, but few have explored this issue in the context of democratization in rural economies. Success in DPD is often determined by the capacity and competence of human resources in the government sector, public service, administration, and socioeconomic empowerment. This study examines the use of Development Planning Deliberation as a participatory communication tool in four agritourism villages of Central Java Province, Indonesia. The study employs a mixed-methods approach, including a questionnaire survey and a qualitative case study. The research findings show that Development Planning Deliberation fosters democratic decision-making, allowing stakeholders to express their aspirations and make decisions based on community needs and issues. Development Planning Deliberation creates a non-discriminatory culture and promotes decision-making based on mutual agreement. This study provides valuable insights into communication studies, highlighting the strategic characteristics required in the development planning process, particularly in the context of democratisation in rural economies.

show abstract

Section: Methodsmentioning

confidence: 99%

The Importance of Participatory Communication in Development Planning Deliberations for Agritourism Village Enhancement

Sulaiman,

Rosyadi,

Handoko

et al. 2024

JICC

View full text Add to dashboard Cite

show abstract

“…Instead, analyzing the context was needed (Tong et al, 2017). We excluded function words and onomatopoeia, then sorted words with an occurrence of ≥50% in each corpus to congregate dominant words as predominantly narrated words and meaning clusters are able to reconstruct the lived experiences (DiMaggio, 2015;Ho et al, 2021;Kozlowski et al, 2019). Results were visualized through Gephi (0.9.6).…”

Section: Methodsmentioning

confidence: 99%

Double-Edged Network Effects on Disclosing Traumatic Experiences Among Korean “Comfort Women”

Kim

Shin

2023

J Interpers Violence

View full text Add to dashboard Cite

This study examines the effects of social networks on the disclosure of stigmatizing and traumatic sexual assault experiences. We analyzed publicly archived oral histories of Korean “comfort women” from World War II, employing an innovative method combining word embedding analysis, word frequency comparison, and grounded theory. By extracting their significant social relationships from narrated survivor stories, we parsed two distinctive disclosure patterns according to timing of disclosure: early disclosers and late disclosers. The latter were more socially embedded than the former, indicating the constraining aspect of social networks, in which the size of social networks was positively associated with delayed disclosure. Qualitative findings further elaborated that social networks have double-edged effects. Survivors’ familial networks functioned as both social constraints and social support for public disclosure. Yet, the late disclosers tend to exploit it more as constraints for the fear of transgenerational transmission of social scorn and stigma. The findings contribute to enhancing a culturally relevant understanding of trauma and the repercussions of human trafficking.

show abstract

“…2. Recent examples of these latter situations are times of crises like the COVID-19 pandemic (Chang et al, 2021;Ho et al, 2021;Poth et al, 2021). The first time LACOID is executed, you may need to select menu "View" and "Force Reload" to generate all paths to this newly extracted folder.…”

Section: Orcid Idmentioning

confidence: 99%

Latent Code Identification (LACOID): A Machine Learning-Based Integrative Framework [and Open-Source Software] to Classify Big Textual Data, Rebuild Contextualized/Unaltered Meanings, and Avoid Aggregation Bias

Canché

2023

International Journal of Qualitative Methods

View full text Add to dashboard Cite

Labeling or classifying textual data and qualitative evidence is an expensive and consequential challenge. The rigor and consistency behind the construction of these labels ultimately shape research findings and conclusions. A multifaceted methodological conundrum to address this challenge is the need for human reasoning for classification that leads to deeper and more nuanced understandings; however, this same manual human classification comes with the well-documented increase in classification inconsistencies and errors, particularly when dealing with vast amounts of documents and teams of coders. An alternative to human coding consists of machine learning-assisted techniques. These data science and visualization techniques offer tools for data classification that are cost-effective and consistent but are prone to losing participants’ meanings or voices for two main reasons: (a) these classifications typically aggregate all texts configuring each input file (i.e., each interview transcript) into a single topic or code and (b) these words configuring texts are analyzed outside of their original contexts. To address this challenge and analytic conundrum, we present an analytic framework and software tool, that addresses the following question: How to classify vast amounts of qualitative evidence effectively and efficiently without losing context or the original voices of our research participants and while leveraging the nuances that human reasoning bring to the qualitative and mixed methods analytic tables? This framework mirrors the line-by-line coding employed in human/manual code identification but relying on machine learning to classify texts in minutes rather than months. The resulting outputs provide complete transparency of the classification process and aid to recreate the contextualized, original, and unaltered meanings embedded in the input documents, as provided by our participants. We offer access to the database ( González Canché, 2022e ) and software required ( González Canché, 2022a , Mac https://cutt.ly/jc7n3OT , and Windows https://cutt.ly/wc7nNKF ) to replicate the analyses. We hope this opportunity to become familiar with the analytic framework and software, may result in expanded access of data science tools to analyze qualitative evidence (see also González Canché 2022b , 2022c , 2022d , for related no-code data science applications to classify and analyze qualitative and textual data dynamically).

show abstract

A Mixed Methods Study of Public Perception of Social Distancing: Integrating Qualitative and Computational Analyses for Text Data

Cited by 14 publications

References 60 publications

The Importance of Participatory Communication in Development Planning Deliberations for Agritourism Village Enhancement

The Importance of Participatory Communication in Development Planning Deliberations for Agritourism Village Enhancement

Double-Edged Network Effects on Disclosing Traumatic Experiences Among Korean “Comfort Women”

Latent Code Identification (LACOID): A Machine Learning-Based Integrative Framework [and Open-Source Software] to Classify Big Textual Data, Rebuild Contextualized/Unaltered Meanings, and Avoid Aggregation Bias

Contact Info

Product

Resources

About