Humanizing Chatbots for Political Campaigns: How Do Voters Respond to Feasibility and Desirability Appeals from Political Chatbots?

Informed by the construal level theory (CLT) and accounting for anthropomorphism, we investigated the effectiveness of political chatbots in influencing voting intentions. This study employed a three-way analysis of variance test with a 2 (anthropomorphism: anthropomorphism vs. non-anthropomorphism) × 2 (message type: feasibility vs. desirability appeal) × 2 (political ideology: conservatives vs. liberals) between-subjects experiment (n = 360). The findings reveal that participants showed higher voting intention after conversing with a highly anthropomorphic chatbot (vs. non-anthropomorphic chatbot) and when the chatbot delivered desirability (vs. feasibility) appeals. Participants also exhibited a higher voting intention when the chatbot was less anthropomorphic and it delivered feasibility (vs. desirability) messages. Moreover, we identified the three-way interaction effects of anthropomorphism, message appeal type and political ideology on voting intention. These findings are discussed in terms of their theoretical and practical implications.