Growing impact of hashtags on rapidly reaching wider audience on social media platforms has called for investigating strategic ways to utilize its power in driving effective consumer engagement and facilitating community feelings attached to the brands. Extant literature has primarily focused on examining how consumers perceive the usage of brand- related hashtags and subsequent attitudinal and behavioral responses to adopt them on their own posts. In line with this effort to uncover the role of brand-related hashtags, such as brand community hashtags, particularly, this dissertation aimed to investigate the role of network structure of individual consumers nested within social media platforms and the interactive relationships with their neighbors that contribute to enhancing brand communication outcomes. Drawing from social identity theory, optimal distinctiveness theory, and consumer-brand relationship literature, consumers' ego networks built through brand community hashtags on Twitter were examined by employing several computational methods, including data mining, social network analysis, computerized textual analysis, and sentiment analysis. The results revealed the positive impact of consumers' ego network size on enhancing content engagement through brand community hashtags in addition to the significant moderating influence of the strength of interpersonal relationship with their network neighbors on facilitating content reach and engagement on Twitter. In particular, findings shed light on understanding consumer roles in the perspectives of networked brand communication, and provide various theoretical and managerial implications.