Electronic Resource
Temporal Sequence of Retweets Help to Detect Influential Nodes in Social Networks
| العنوان: | Temporal Sequence of Retweets Help to Detect Influential Nodes in Social Networks |
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| المؤلفون: | UCL - SST/ICTM/INMA - Pôle en ingénierie mathématique, Bhowmick, Ayan Kumar, GUEUNING, Martin, Delvenne, Jean-Charles, Lambiotte, Renaud, Mitra, Bivas |
| المصدر: | IEEE Transactions on Computational Social Systems, Vol. 6, no.3, p. 441-455 (2019) |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE) 2019 |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | Identification of influential users in online social networks allows to facilitate efficient information diffusion to a large part of the network and thus benefiting diverse applications including viral marketing, disease control, and news dissemination. Existing methods have mainly relied on the network structure only for the detection of influential users. In this paper, we enrich this approach by proposing a fast, efficient, and unsupervised algorithm SmartInf to detect a set of influential users by identifying anchor nodes from a temporal sequence of retweets in Twitter cascades. Such anchor nodes provide important signatures of tweet diffusion across multiple diffusion localities and, hence, act as precursors for detection of influential nodes. 1 The set of influential nodes identified by SmartInf has the capacity to expose the tweet to a large and diverse population, when targeted as seeds thereby maximizing the influence spread. Experimental evaluation on empirical datasets from Twitter shows the superiority of SmartInf over state-of-the-art baselines in terms of infecting larger population; further, our evaluation shows that SmartInf is scalable to large-scale networks and is robust to missing data. Finally, we investigate the key factors behind the improved performance of SmartInf by testing our algorithm on a synthetic network using synthetic cascades simulated on this network. Our results reveal the effectiveness of SmartInf in identifying a diverse set of influential users that facilitate faster diffusion of tweets to a larger population. 1 We use the terms “influential nodes” and “influential users” interchangeably. |
| مصطلحات الفهرس: | Human-Computer Interaction, Modelling and Simulation, Social Sciences (miscellaneous), info:eu-repo/semantics/article |
| URL: | |
| الاتاحة: | Open access content. Open access content info:eu-repo/semantics/openAccess |
| ملاحظة: | English |
| Other Numbers: | UCDLC oai:dial.uclouvain.be:boreal:217752 boreal:217752 info:doi/10.1109/tcss.2019.2907553 urn:EISSN:2373-7476 1130443616 |
| المصدر المساهم: | UNIVERSITE CATHOLIQUE DE LOUVAIN From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: | edsoai.on1130443616 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |