Machine Learning in Action: DivPSM Enhances Analysis of Diversity Communication on Social Media

Researchers from multiple Dutch universities developed the Diversity Perspectives in Social Media (DivPSM) tool, using machine learning to analyze organizational diversity communication on social media. DivPSM reveals insights into diversity dimensions and perspectives, highlighting gender diversity's link to innovation and LHGBTQ+ diversity's association with moral perspectives.

In the dynamic landscape of organizational communication, a new digital tool named Diversity Perspectives in Social Media (DivPSM) has emerged as a pivotal innovation for automated content analysis of diversity communication on social media. Developed by researchers from Erasmus University Rotterdam, Amsterdam University of Applied Sciences, University of Amsterdam, Tilburg University, and VU University Amsterdam, this tool employs supervised machine learning to analyze social media posts from organizations, identifying and categorizing references to diversity and related perspectives. DivPSM stands out as a significant advancement in the study of strategic diversity communication, addressing the need for scalable and efficient analysis methods in the era of big data.

Revolutionizing Diversity Analysis with DivPSM

The paper introduces DivPSM and meticulously details its training and validation processes. The tool is designed to recognize three key dimensions of diversity: cultural/ethnic/racial, gender, and LHGBTQ+, as well as three diversity perspectives: moral, market, and innovation. In the first study presented, the researchers validate the tool's accuracy by comparing its performance to that of human coders, confirming its reliability for future research. This validation process involved a robust methodology, including the development of a manual codebook, intercoder reliability testing, and the use of advanced machine-learning algorithms like BERT (Bidirectional Encoder Representations from Transformers). The validation results showed high levels of accuracy and reliability, establishing DivPSM as a credible tool for diversity communication analysis.

Insights from Analyzing Dutch Organizations' Social Media

Study 2 illustrates the practical application of DivPSM by analyzing a substantial dataset of 84,561 social media posts from large Dutch organizations. The findings reveal that gender diversity is the most frequently mentioned dimension in these posts, followed by LHGBTQ+ and cultural/ethnic/racial diversity. Additionally, the innovation perspective is the most prevalent among diversity-related posts, indicating a strong association between gender diversity and innovation. In contrast, LHGBTQ+ diversity is more often linked to moral perspectives. These insights highlight the nuanced ways organizations communicate about diversity and suggest that different dimensions of diversity are associated with distinct underlying motivations.

Strategic Diversity Communication as a Driver of Change

The research highlights the evolving role of strategic diversity communication as a driver of social change and organizational innovation. It underscores the significance of understanding the interplay between different diversity dimensions and perspectives, suggesting that organizations perceive and communicate these aspects in distinct ways. This understanding is crucial for developing effective diversity management strategies and for fostering an inclusive organizational culture. Theoretical implications of this research include the potential of diversity communication to influence both organizational practices and societal attitudes. The study aligns with recent theoretical advances in formative CSR communication, which posits that communication and practices are mutually constitutive and influence each other over time.

Future Directions for DivPSM and Diversity Research

Future directions for DivPSM involve enhancing its accuracy and expanding its applicability to other social media platforms and languages. Currently, the tool is limited to analyzing English-language posts and three diversity dimensions. However, the researchers aim to extend its capabilities to include other important dimensions such as age, religious diversity, neurodiversity, and inclusion of employees with disabilities. Additionally, incorporating multilingual models would enable more comprehensive cross-national comparisons and a deeper understanding of how strategic diversity communications affect different stakeholder groups globally.

DivPSM represents a significant advancement in the field of diversity research, offering scholars a valuable resource for large-scale, automated analysis of organizational communication. The open-source nature of DivPSM encourages its use and adaptation by the broader research community, promising to advance our understanding of strategic diversity communication and its role in fostering equality and inclusion in the workplace. The tool's development marks a significant step forward in diversity research, providing new opportunities for scholars to explore the complex dynamics of diversity communication and its impact on organizational and societal outcomes. With continued refinement and expansion, DivPSM has the potential to significantly contribute to the ongoing efforts to promote diversity and inclusion in organizations worldwide.