[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83380-en":3,"doc-seo-83380-105":29,"detail-sidebar-cat-0-en-105":82},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},83380,1099514068365,"Aurelia","https://ap-avatar.wpscdn.com/avatar/10000253d8d9f28188e?_k=1776742907772140068",8,"Research & Report","Does Online Sustainability Communication Shape Public Discourse? Insights from Six Years of Tenant-Housing Provider Interactions","Authorities increasingly rely on social media to support sustainability transitions, infrastructure investment, and service reform, yet citizen responses remain insufficiently understood. This study builds a data-driven multidimensional framework to examine how sustainability-related posts influence discourse content in Dutch public housing. Using 792 posts and 3,197 tenant comments from 92 providers (2018–2023), a machine-learning pipeline classifies comments across communicative intent, sentiment, and semantic relatedness, then models effects with multinomial logistic regression.","arXiv :2607 .08437v 1 [ cs .CY] 9 Jul 2026  \nDoes online sustainability communication shape public discourse? Insights from six years oftenant-housing provider interactions  \nShray Juneja 1,* , Suzan Verberne2 , and Ioulia V. Ossokina 1  \n1 Eindhoven University of Technology, the Netherlands  \n2 Leiden University, the Netherlands  \n* [s.juneja@tue.nl](s.juneja@tue.nl)  \nABSTRACT  \nAuthorities increasingly rely on social media to advance sustainability transitions, infrastructure investment, and service reform. Yet how citizens respond to these digital communications remains poorly understood. Existing approaches rely on aggregate engagement metrics (e.g., likes), providing limited insight into discourse structure and quality. We developed a data-driven, multidimensional framework to analyse how social media communication shapes the content of discourse, focusing on sustainability-related engagement in Dutch public housing. We analysed 792 posts and 3,197 tenant comments from the Facebook pages of 92 housing providers (2018-2023) . A machine-learning pipeline classified comments into recurring discourse configurations across three dimensions-communicative intent, sentiment, and semantic relatedness. Multinomial logistic regression estimated the effects of post-design and organisational characteristics on discourse. Tenant comments were significantly more semantically aligned with their corresponding posts than with randomly paired content, indicating that organisational communication structures responses to topics. Six discourse types emerged, with critical and inquiry-driven engagement increasing over time. Post-level features did not significantly explain variation; organisational characteristics dominated. Larger housing associations attracted more substantive responses, while lower-rent organisations received fewer evaluative comments. While applied to housing associations, our methodology provides a scalable approach to analyse online discourse dynamics, quality, and content across organisations and contexts.  \nKeywords: Social media communication; Online discourse typology; Citizen engagement; Machine learning; Sustainability transitions; Public housing  \n1 Introduction  \nSocial media has become a central arena through which organisations communicate with citizens on consequential public issues, including sustainability transitions, infrastructure investment, and service reform. In these contexts, communication is not merely informational but constitutive: it shapes how citizens interpret policy, evaluate legitimacy, and decide whether to engage [1, 2] . A growing body of research shows that the content and quality of online communication influence both citizen participation [3, 4] and the effectiveness of organisational initiatives [5, 6] .  \nMost existing research has measured audience response using aggregate metrics such as likes, comments, and shares, which capture participation volume but obscure its qualitative nature [6–12] . Under these metrics, distinct forms of engagement, such as critical evaluation, information seeking, or passive redistribution, can appear equivalent, even though responses vary in affect, communicative function, and alignment with the original message. The multidimensionality of organisational communication matters for legitimacy, trust, and policy outcomes [13, 14], yet existing approaches have failed to capture it, thereby limiting understanding of how organisational communication shapes public discourse.  \nTypology-based approaches present a promising alternative by classifying discourse into distinct modes of engagement. However, existing typologies have typically been qualitative or theoretically derived and have relied on corpus-based approaches to capture discourse variation [15–17] or operationalisation along a single dimension, such as sentiment [4] or topic modelling [18] . 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