Sentiment analysis as tool for gender mainstreaming in slum rehabilitation housing management in Mumbai, India

摘要: Abstract Gender mainstreaming in slum rehabilitation is a critical determinant for the success or failure of it. Slum Mumbai hallmark example participatory process which supposed to improve quality life and well-being among rehabilitated occupants, on paper. Yet our findings show that key stakeholders’ (i.e. policymaker, architect, management co-operatives female occupants) sentiments are worlds apart. This gap evokes need more systematic framework approach. Verbal communication has power implicitly decipher common emotion sentiment regarding infrastructure its related policy. study uses quasi-qualitative approach understand underlying concerns gender housing (SRH) Mumbai, India. narratives from semi-structured interviews focus group discussions used explore stakeholders. Sentiment analysis using machine learning technique Natural Language Processing (NLP) decode emotions across The results indicate inequality SRH propagated through lack different vocabulary by occupants apex policymakers. There also remarkable differences between male- female-led who charge management. Female-led were observed go beyond basic maintenance duties, reduce debt monthly fees take up incremental improvements such as decorative elements installation solar panels. participation required full body co-operative rather than partial representation order be effective. suggests important not only design but exploring stakeholders, proposed analysis, could mitigate undesirable effects enable process.