Human interactions create social networks forming the backbone of societies. Individuals adjust their opinions by exchanging information through social interactions. Two recurrent questions are whether social structures promote opinion polarisation or consensus in societies and whether polarisation can be avoided, particularly on social media. In this paper, we hypothesise that not only network structure but also the timings of social interactions regulate the emergence of opinion clusters. We devise a temporal version of the Deffuant opinion model where pairwise interactions follow temporal patterns and show that burstiness alone is sufficient to refrain from consensus and polarisation by promoting the reinforcement of local opinions. Individuals self-organise into a multi-partisan society due to network clustering, but the diversity of opinion clusters further increases with burstiness, particularly when individuals have low tolerance and prefer to adjust to similar peers. The emergent opinion landscape is well-balanced regarding clusters' size, with a small fraction of individuals converging to extreme opinions. We thus argue that polarisation is more likely to emerge in social media than offline social networks because of the relatively low social clustering observed online. Counter-intuitively, strengthening online social networks by increasing social redundancy may be a venue to reduce polarisation and promote opinion diversity.

翻译：人际互动构建了支撑社会的社会网络。个体通过社会互动交换信息来调整自身观点。两个反复出现的问题是：社会结构是促进社会中的意见极化还是共识，以及极化是否可以避免，尤其是在社交媒体上。本文假设，不仅网络结构，而且社会互动的时间节奏也调节着意见簇的形成。我们设计了一个时间版本的Deffuant意见模型，其中成对互动遵循时间模式，并证明仅爆发性就足以通过促进局部意见的强化来避免共识和极化。由于网络聚类，个体自组织形成多党派社会，但意见簇的多样性随爆发性进一步增加，尤其当个体容忍度低且倾向于与相似同伴调整意见时。最终意见景观在簇的规模上保持良好平衡，仅少数个体趋于极端观点。因此，我们认为极化更可能出现在社交媒体而非线下社交网络中，因为线上观察到的社会聚类相对较低。反直觉的是，通过增加社会冗余来强化在线社交网络，可能是减少极化并促进意见多样性的途径。