Plans Versus Political Priorities: Lessons from Municipal Election Candidates’ Social Media Communications

Abstract

Problem, research strategy, and findings Local elected officials play a leadership role in setting plan directions and can jeopardize implementation if they are not committed to plan goals. In this research, we apply topic modeling, semantic networks, and sentiment analyses to Calgary's (Canada) plans and candidates' social media communications in the 2017 Calgary municipal election to assess alignments or divergences between plans' and candidates' priorities. Though the mayor, ward representatives, incumbents, and challengers prioritized different topics, we find overall support for transit infrastructure, development, and improving the downtown and the municipal tax base. However, candidates showed little interest in environmental issues, growth management, and regional cooperation, which are important plan goals that may not be addressed. The methodology has limitations: Using social media posts underrepresents the views of some candidates; text data processing may miss metaphorical phrases; elected officials' priorities during campaigns may not determine their actual votes once in office; and this cross-sectional analysis does not capture the ever-changing relations between officials' priorities, plan-making, and implementation. Takeaway for practice Candidates focused mainly on transit and taxes to the detriment of regional and environmental issues (energy, watershed, and growth management), revealing the incoming municipal administration's priorities and its potential blind spots. Planners may use this methodology to analyze large text data from both online and offline sources, understand local implementation barriers, explain shifts in municipal policy directions, and engage elected officials to build support for important plan components. Keywords content analysis, elections, plans, social media, text mining