Sensemaking and lens-shaping: Identifying citizen contributions to foresight through comparative topic modelling

• This research uses natural language processing (Topic Modelling) to identifying novel contributions from participatory foresight workshops. Computational textual analysis offers insights emerging comparisons of expert and citizen based products. Natural Language Processing (NLP) technologies offer new modes examining texts for sensemaking purposes in organizations. can reshape organizational factors affecting through sourced inputs. As activities continue increase across multiple arenas types organizations, the need develop effective reviewing future-oriented information against long-term goals policies becomes more pressing. The institutional are vital constructing potential desired futures, but remain sensitive culture ethos, thus raising concerns about whose futures being constructed. In viewing studies as a critical component such sensemaking, this investigates method that deploys algorithms (NLP). research, we introduce apply methodology topic modelling conducting comparative explore how citizen-derived differs other foresight. Finally present prospects further employing NLP strategic studies.