# Application of Text Analytics in Public Service Co-Creation: Literature Review and Research Framework

arXiv: https://arxiv.org/abs/2305.18316 · HTML: https://mlsanity.com/paper/2305.18316/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 108 references that are in the map.
- First posted on arXiv 20 May 2023.

## Builds on (most cited first, 4 of 4)

- [Citizen Participation and Machine Learning for a Better Democracy](https://mlsanity.com/paper/2103.00508/) (2021)
- [Legal Document Retrieval using Document Vector Embeddings and Deep Learning](https://mlsanity.com/paper/1805.10685/) (2018)
- [Identifying Relationships Among Sentences in Court Case Transcripts Using Discourse Relations](https://mlsanity.com/paper/1809.03416/) (2018)
- [An affective and adaptive educational robot](https://mlsanity.com/paper/2205.10222/) (2022)

## Abstract (arXiv)

The public sector faces several challenges, such as a number of external and internal demands for change, citizens' dissatisfaction and frustration with public sector organizations, that need to be addressed. An alternative to the traditional top-down development of public services is co-creation of public services. Co-creation promotes collaboration between stakeholders with the aim to create better public services and achieve public values. At the same time, data analytics has been fuelled by the availability of immense amounts of textual data. Whilst both co-creation and TA have been used in the private sector, we study existing works on the application of Text Analytics (TA) techniques on text data to support public service co-creation. We systematically review 75 of the 979 papers that focus directly or indirectly on the application of TA in the context of public service development. In our review, we analyze the TA techniques, the public service they support, public value outcomes, and the co-creation phase they are used in. Our findings indicate that the TA implementation for co-creation is still in its early stages and thus still limited. Our research framework promotes the concept and stimulates the strengthening of the role of Text Analytics techniques to support public sector organisations and their use of co-creation process. From policy-makers' and public administration managers' standpoints, our findings and the proposed research framework can be used as a guideline in developing a strategy for the designing co-created and user-centred public services.