Social network analytics and visualization: Dynamic topic‐based influence analysis in evolving micro‐blogs

Abstract

Influence Analysis is one of the well‐known areas of Social Network Analysis. However, discovering influencers from micro‐blog networks based on topics has gained recent popularity due to its specificity. Besides, these data networks are massive, continuous and evolving. Therefore, to address the above challenges we propose a dynamic framework for topic modelling and identifying influencers in the same process. It incorporates dynamic sampling, community detection and network statistics over graph data stream from a social media activity management application. Further, we compare the graph measures against each other empirically and observe that there is no evidence of correlation between the sets of users having large number of friends and the users whose posts achieve high acceptance (i.e., highly liked, commented and shared posts). Therefore, we propose a novel approach that incorporates a user's reachability and also acceptability by other users. Consequently, we improve on graph metrics by including a dynamic acceptance score (integrating content quality with network structure) for ranking influencers in micro‐blogs. Additionally, we analysed the topic clusters' structure and quality with empirical experiments and visualization.

A Comprehensive Overview of Micro-Influencer Marketing: Decoding the Current Landscape, Impacts, and Trends

“…The analysis reveals a need for more in-depth and refined research on micro-influencers. Several articles emphasize the crucial role of “credibility” in the current micro-influencer mechanism [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ], with this paper addressing the antecedents of “credibility” and bridging gaps in micro-influencer identification compared to other influencers.…”

“…As expected, the dominant platform for micro-influencers is social media, as indicated in the table, where 24 out of 34 authors opted for Instagram, amassing a total sample size of 9053, while e-commerce platforms have limited representation. The very spaces used for daily documentation, self-expression, entertainment, and social connections consistently serve as arenas for consumption [ 2 , 5 , 6 , 7 , 9 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 43 , 59 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 ]. This highlights the influence of micro-influencers on their followers’ consumption patterns in three ways: first, through the presentation of consumption content reinforcing media discourse to consumers; second, by emphasizing how social media fundamentally shapes the contemporary landscape of consumption, creating digital consumption scenes at any time and place, influencing user behavior, and reshaping consumer demographics; and third, the proliferation of short videos and live streaming platforms, which has disrupted the media system, with micro-influencers acting as catalysts continuously impacting and rebalancing power dynamics across various digital media forms [ 83 ].…”

Applications of Social Network Analysis in Promoting Circular Economy: A Literature Review

“…In this sense, SNA coincides with practical scenarios that require the study of interaction patterns between multiple stakeholders. SNA involves three aspects of research contents: 1) network structure, e.g., network modeling methods (Xu et al, 2021;Sweet & Adhikari, 2022), quantitative analysis of statistical measures (Marques & Manzanares, 2022), community detection (Mansoureh et al, 2022), 2) the actors (stakeholders) on the network, e.g., individual influence analysis (Tabassum et al, 2022), opinion mining (Zarrabeitia-Bilbao et al, 2022), 3) information on the network, e.g., information diffusion model (Granovetter, 1978). As shown in Figure 2, the network structure is the carrier for the interactive relations of actors and the information flow.…”

An effective overlapping community merging method oriented to multidimensional attribute social networks

“…Microblog is a typical social network integrating communication, convenience, timeliness and entertainment (Tabassum et al, 2022). It is of great significance to analyse Microblog users' relationships, mine Microblog content and optimize network structure for us to detect Microblog community.…”