Reconstructing the decision-making processes of a city council based on references between documents

Council members and policy workers need to understand (long-term) processes that lead to decisions. Gaining such an overview of a topic through a search engine can be challenging however, as searching a complex topic can result in an overwhelming number of documents and does not show how these documents are interrelated. This study investigates how to create an overview of a decision-making process, which may be integrated into a search engine. Interviews show that policy workers consider documents relevant to the overview when the document and proposal were both created in response to the same council decision document. We identify such provenance based on the co-citation of documents and textual references between documents. In an exploratory user study, policy workers are tasked to understand the development of policy proposals based on provided timelines. Their relevance assessments show that our approach nearly exclusively finds relevant documents (a precision of 0.97). Whereas the proposed approach identifies 91% of references made in documents, it only finds an exact target document in 39% of the total references. A further 52% of references finds a subset of documents including the target. A human in the loop can aid in finding the exact documents, and potentially add documents based on their domain expertise. The proposed approach creates an overview of a city council’s decision-making process on a given topic with high precision, and might apply to other domains oriented around a decision-making process.

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