推文中的人们:在线集体身份叙事与时间性——以#黎巴嫩革命为例

People on the tweets: Online collective identity narratives and temporality in the #LebaneseRevolution

ORGANIZATION · 2022
被引 12
人大 A-ABS 3

中文导读

研究了2019年黎巴嫩十月革命期间Twitter上集体身份在叙事中的形成过程,通过主题和叙事分析揭示了过去、现在和未来时间线索交织的在线身份叙事,并识别出三种时间主题类别。

Abstract

Our study examines collective identity development in the early stages of a social movement as it narratively unfolded on Twitter during the 2019 October revolution in Lebanon. Based on a sample extraction of Twitter content from the first month of the revolution and using both thematic and narrative analyses, our study uncovers an entangled temporality where past, present and future strands of narrative time intervene in online identity narratives. Disentangling these digital narratives enabled us to identify three temporal-thematic categories that outline the contours of the emergent online identity: a revisited narrative past evoking collective nostalgia, a disruptive narrative present creating an urgent “presence in the now,” and a prefigurative narrative future that allows online members to collectively re-imagine and co-create their collective selfhood. Taken together, these findings support better understandings of collective identity emergence in digitally-mediated social movements in three different ways. First, building on the organizational literature on temporality in collective identity formation, we highlight how temporal narratives online support and accelerate a nascent collective identity through their immediacy and global reach. Second, by approaching narrated time theoretically and not chronologically, we address recent calls that challenge linear temporal narratives. We highlight how entangled temporality contributes to the emergence of a social movement’s online collective identity. Ultimately, from a methodological perspective, we offer an approach for “disentangling” digital temporality and propose (ante)narrative theory as a useful interpretive lens for better apprehending identity-relevant social media content.

社会运动集体身份社交媒体叙事分析时间性