Replication Data for: Learning from the other side: how social networks influence turnout in a referendum campaign

Interpersonal discussion is considered to be one of the most influential sources of opinion formation and behaviour. Yet, an unresolved puzzle remains within the literature: while some studies show that discussion with not like-minded citizens depresses political participation, other studies, on the contrary, indicate that the same type of interpersonal discussion can foster political engagement. In this study, we address this unresolved democratic dilemma for the first time in a context of direct democracy, by focussing on the campaign leading to the 2016 Italian constitutional referendum. Specifically, we pay particular attention to the interaction between network diversity, ambivalence and political knowledge. The findings show that frequent interactions with not like-minded citizens increase turnout. The results based on regression models and structural equation modelling indicate that this positive effect is channelled mainly through political learning, since network diversity increases factual knowledge about the constitutional reform, which in turn is associated with an increase in turnout. We do not find a significant effect of network diversity on ambivalence, as predicted by previous studies. These findings have important implications for deliberative theories and campaign strategies.

人际讨论被视为影响个体意见形成与行为选择的最具影响力的来源之一。然而，现有学界研究仍存在一个尚未解决的谜题：部分研究显示，与政见相左的公民进行讨论，会抑制政治参与；而另一部分研究则得出相反结论，认为此类人际讨论反而能提升政治投入。本研究首次在直接民主（direct democracy）语境下，聚焦2016年意大利宪法全民公投的竞选活动，针对这一未决的民主困境展开探讨。我们重点关注网络多样性、态度矛盾性与政治知识三者间的交互作用。研究结果显示，与政见相左的公民高频互动可提升投票率。基于回归模型与结构方程模型（structural equation modelling）的分析结果表明，这一正向效应主要通过政治学习得以传导：网络多样性提升了民众对此次宪法改革的事实性认知，而此类认知的提升又与投票率的提高呈显著正相关。我们未发现如既往研究所预测的，网络多样性对态度矛盾性存在显著影响。上述发现对协商民主理论（deliberative theories）与竞选策略均具有重要的理论与实践启示。