In this paper, we present CAROL (unConventionAl suRvey methOdoLogy) to collect users’ opinions, to analyze them effectively, and to graphically provide interesting summaries in near-real-time. CAROL has been designed to collect citizens’ opinions, needs, and a perception that can be very useful to redesign cities and drive the innovation process. To this aim, particular importance is given to the architecture implemented to collect the data, which involves sending voice messages instead of text, allowing users greater freedom of expression. Moreover, to make the survey more friendly, an initial analysis is done in real-time thanks to an intuitive dashboard, which shows the first results in the form of graphs and charts, updated after each message. Finally, a more in-depth analysis can be carried out at the end of the survey, thanks to text-mining techniques adapted to the context. As use case, the proposed methodology has been tested in a public event organized by Politecnico di Torino and addressed to female students, with the aim to collect their ideas about new services/opportunities that can be offered to support women in STEM

Proactive user engagement via friendly survey and data-driven methodologies / Bethaz, Paolo; Callà, Riccardo; Cerquitelli, Tania; Montorsi, Arianna; De Giorgi, Claudia. - ELETTRONICO. - (2020), pp. 56-63. ((Intervento presentato al convegno International Conference on Data Engineering (ICDE) 2020 nel 20-24 April 2020 [10.1109/ICDEW49219.2020.000-7].

Proactive user engagement via friendly survey and data-driven methodologies

Bethaz Paolo;Callà Riccardo;Cerquitelli Tania;Montorsi Arianna;De Giorgi Claudia
2020

Abstract

In this paper, we present CAROL (unConventionAl suRvey methOdoLogy) to collect users’ opinions, to analyze them effectively, and to graphically provide interesting summaries in near-real-time. CAROL has been designed to collect citizens’ opinions, needs, and a perception that can be very useful to redesign cities and drive the innovation process. To this aim, particular importance is given to the architecture implemented to collect the data, which involves sending voice messages instead of text, allowing users greater freedom of expression. Moreover, to make the survey more friendly, an initial analysis is done in real-time thanks to an intuitive dashboard, which shows the first results in the form of graphs and charts, updated after each message. Finally, a more in-depth analysis can be carried out at the end of the survey, thanks to text-mining techniques adapted to the context. As use case, the proposed methodology has been tested in a public event organized by Politecnico di Torino and addressed to female students, with the aim to collect their ideas about new services/opportunities that can be offered to support women in STEM
978-1-7281-4266-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2847739