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Many organisations, including professional councils, operate manually to ensure document flow to clients and stakeholders. This results in the loss of valuable documentation such as certificates and the incurring of costs due to the returning of post to the sender. The purpose of this study was to explore digital transformation of document flow at the South African Council for Social Science Professionals.

The methodological approach involved qualitative data collected through interviews, observation and document analysis in response to research questions. The study was a participatory action research project that involved collaboration between researchers and study participants in defining and solving the problem through needs assessment exercise. All three phases of participatory action research were followed, namely, the “look phase”: getting to know stakeholders so that the problem is defined on their terms and the problem definition is reflective of the community context; the “think phase”: interpretation and analysis of what was learned in the “look phase” and the “act phase”: planning, implementing, and evaluating, based on information collected and interpreted in the first two phases.

The study identified various issues relating to poor data quality, high rate of registered postal returns and non-delivery electronic messages that cannot reach all the intended recipients and accumulation of data for decades. In this regard, the study proposes a framework that can be used by SACSSP to update and verify their details on the portal, as well as digital certificates for membership.

Although the proposed framework is tailor-made for the professional council, it is not depended on prescribed technologies due to usage of open standards that can be used by industry and researchers. Therefore, it can be applied in other context where institutions such as universities communicate with many clients via postal or courier services.

The study used participatory action research involving the researchers and the organisation to solve the problem. The study presented a workflow that the council can use to ensure that the documents reach intended recipients. Furthermore, digital transformation of the process will ensure that the registered professionals are able to access their certificates online and can print them when necessary.

Grounded in the stakeholder theory and signaling theory, this study aims to broaden the research agenda on environmental, social and governance (ESG) investing by uncovering public sentiments and key themes using Twitter data spanning from 2009 to 2022.

Using various machine learning models for text tonality analysis and topic modeling, this research scrutinizes 1,842,985 Twitter texts to extract prevalent ESG investing trends and gauge their sentiment.

Gibbs Sampling Dirichlet Multinomial Mixture emerges as the optimal topic modeling method, unveiling significant topics such as “Physical risk of climate change,” “Employee Health, Safety and well-being” and “Water management and Scarcity.” RoBERTa, an attention-based model, outperforms other machine learning models in sentiment analysis, revealing a predominantly positive shift in public sentiment toward ESG investing over the past five years.

This study establishes a framework for sentiment analysis and topic modeling on alternative data, offering a foundation for future research. Prospective studies can enhance insights by incorporating data from additional social media platforms like LinkedIn and Facebook.

Leveraging unstructured data on ESG from platforms like Twitter provides a novel avenue to capture company-related information, supplementing traditional self-reported sustainability disclosures. This approach opens new possibilities for understanding a company’s ESG standing.

By shedding light on public perceptions of ESG investing, this research uncovers influential factors that often elude traditional corporate reporting. The findings empower both investors and the general public, aiding managers in refining ESG and management strategies.

This study marks a groundbreaking contribution to scholarly exploration, to the best of the authors’ knowledge, by being the first to analyze unstructured Twitter data in the context of ESG investing, offering unique insights and advancing the understanding of this emerging field.

In this article, the author discusses works from the French Documentation Movement in the 1940s and 1950s with regard to how it formulates bibliographic classification systems as documents. Significant writings by Suzanne Briet, Éric de Grolier and Robert Pagès are analyzed in the light of current document-theoretical concepts and discussions.

Conceptual analysis.

The French Documentation Movement provided a rich intellectual environment in the late 1940s and early 1950s, resulting in original works on documents and the ways these may be represented bibliographically. These works display a variety of approaches from object-oriented description to notational concept-synthesis, and definitions of classification systems as isomorph documents at the center of politically informed critique of modern society.

The article brings together historical and conceptual elements in the analysis which have not previously been combined in Library and Information Science literature. In the analysis, the article discusses significant contributions to classification and document theory that hitherto have eluded attention from the wider international Library and Information Science research community. Through this, the article contributes to the currently ongoing conceptual discussion on documents and documentality.