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Topic-aware social influence propagation models

Nicola Barbieri, Francesco Bonchi, Giuseppe Manco
2013 Knowledge and Information Systems  
We study social influence from a topic modeling perspective.  ...  We introduce novel topic-aware influence-driven propagation models that experimentally result to be more accurate in describing real-world cascades than the standard propagation models studied in the literature  ...  SIMPLE TOPIC-AWARE PROPAGATION MODELS As a first step towards topic-aware modeling of social influence, we extend the classic IC and LT models to their topic-aware versions.  ... 
doi:10.1007/s10115-013-0646-6 fatcat:qstf27iefrapjksld3p4incsfa

Topic-aware Social Influence Minimization

Qipeng Yao, Ruisheng Shi, Chuan Zhou, Peng Wang, Li Guo
2015 Proceedings of the 24th International Conference on World Wide Web - WWW '15 Companion  
We first employ the HDP-LDA and KL divergence to analysis the influence and relevance from a topic modeling perspective.  ...  In this paper, we address the problem of minimizing the negative influence of undesirable things in a network by blocking a limited number of nodes from a topic modeling perspective.  ...  PROBLEM FORMULATION To model the topic-aware social influence, we adopt the Topic-aware Independent Cascade (TIC) Model [1] , where the user-to-user influence probabilities depend on the topic.  ... 
doi:10.1145/2740908.2742767 dblp:conf/www/YaoSZWG15 fatcat:omn2tnf5rba7pby4vyomt55tpy

Information propagation in microblog networks

Chenyi Zhang, Jianling Sun, Ke Wang
2013 Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - ASONAM '13  
In this paper, we present a topic-aware solution to information propagation in a microblog network.  ...  This approach is topic-aware in that the target message finds its way of propagation according to its topic relevance to the latent topic structure in the network.  ...  Topic modeling has been used to predict social influences between users.  ... 
doi:10.1145/2492517.2492608 dblp:conf/asunam/ZhangSW13 fatcat:6ab5qtacpfartlpjmcpmwqninu

Influence Maximization in Social Networks: A Survey of Behaviour-Aware Methods [article]

Ahmad Zareie, Rizos Sakellariou
2022 arXiv   pre-print
Several approaches have been proposed to estimate users' influence and identify sets of influential users in social networks.  ...  This paper attempts to cover this gap by reviewing and proposing a taxonomy of such behaviour-aware methods to identify influential users in social networks.  ...  Inspired from fluid dynamics, a diffusion model is proposed to simulate propagation in a social network.  ... 
arXiv:2108.03438v2 fatcat:alen2s5sbzaqdkdyux5bqbeysi

Deep Reinforcement Learning-Based Approach to Tackle Topic-Aware Influence Maximization

Shan Tian, Songsong Mo, Liwei Wang, Zhiyong Peng
2020 Data Science and Engineering  
To this end, we first propose two topic-aware social influence propagation models based on IC and LT model, respectively, which is conducive to better advertising injections.  ...  Motivated by the application of viral marketing, the topic-aware influence maximization (TIM) problem has been proposed to identify the most influential users under given topics.  ...  topics G (S| ) The targeted influence spread by S for social graph G under query topics Topic-Aware IC Model Independent cascade (IC) is a classic and well-studied propagation model.  ... 
doi:10.1007/s41019-020-00117-1 fatcat:spzg3smjjzhzhfwiixvqrhbvxe

OCTOPUS: An Online Topic-Aware Influence Analysis System for Social Networks

Ju Fan, Jiarong Qiu, Yuchen Li, Qingfei Meng, Dongxiang Zhang, Guoliang Li, Kian-Lee Tan, Xiaoyong Du
2018 2018 IEEE 34th International Conference on Data Engineering (ICDE)  
This paper presents OC-TOPUS that offers social network users and analysts valuable insights through topic-aware social influence analysis services. OCTOPUS has the following novel features.  ...  Second, OCTOPUS provides three powerful keyword-based topic-aware influence analysis tools: keyword-based influential user discovery, personalized influential keywords suggestion, and interactive influential  ...  Topic-Aware Influence Modeling. Based on the social graph and action logs, OCTOPUS devises a topic-aware social influence model.  ... 
doi:10.1109/icde.2018.00178 dblp:conf/icde/FanQLMZLTD18 fatcat:tkk5f37ws5ab7day4slsascvda

Personalized time-aware tweets summarization

Zhaochun Ren, Shangsong Liang, Edgar Meij, Maarten de Rijke
2013 Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '13  
We propose a time-aware user behavior model, the Tweet Propagation Model (TPM), in which we infer dynamic probabilistic distributions over interests and topics.  ...  Specifically, we consider the task of time-aware tweets summarization, based on a user's history and collaborative social influences from "social circles."  ...  We write TPM-SOC for the model that only considers users' social influence (so excluding time-aware topic propagation and it doesn't consider if some topic is private or not).  ... 
doi:10.1145/2484028.2484052 dblp:conf/sigir/RenLMR13 fatcat:au6wrfzrnjc7jj76l7ctmvnopm

Topic-Aware Physical Activity Propagation in a Health Social Network

Nhathai Phan, Javid Ebrahimi, Dave Kil, Brigitte Piniewski, Dejing Dou
2016 IEEE Intelligent Systems  
Dave Kil, Civitas Learning Brigitte Piniewski, PeaceHealth Laboratories Dejing Dou, University of Oregon Modeling physical activity propagation, such as physical exercise level and intensity, is the key  ...  to preventing the conduct that can lead to obesity; it can also help spread wellness behavior in a social network. week. 2 However, less than 50 percent of the adult population meets these standards in  ...  Our approach, the Topic-aware Communitylevel Physical Activity Propagation (TaCPP) model, is designed to capture the social influences of messages in the YesiWell study.  ... 
doi:10.1109/mis.2015.92 pmid:27087794 pmcid:PMC4830439 fatcat:urndqw5rwfbttcv3qng4mw36iu

Crowd-Sensing with Polarized Sources

Md Tanvir Al Amin, Tarek Abdelzaher, Dong Wang, Boleslaw Szymanski
2014 2014 IEEE International Conference on Distributed Computing in Sensor Systems  
In contrast to previous work on the topic, we consider a model where the sources in question are polarized.  ...  Our analysis of the data set shows the presence of two clearly defined camps in the social network that tend of propagate largely disjoint sets of claims (which is indicative of polarization), as well  ...  Topic-based models to infer user influence and information propagation have been studied in different contexts. Lin et al.  ... 
doi:10.1109/dcoss.2014.23 dblp:conf/dcoss/AminAWS14 fatcat:y34xhpivuraslkewqb7owmewnm

Targeted Influence Maximization Based on Cloud Computing over Big Data in Social Networks

Shiyu Chen, Xiaochun Yin, Qi Cao, Qianmu Li, Huaqiu Long
2020 IEEE Access  
First, a new topic-aware model called tag-aware IC model is presented, which takes into account users' interests, characteristics of the item being propagated, and the similarity between users and the  ...  INDEX TERMS Social network, influence maximization, cloud computing.  ...  In this paper, a new topic-aware model, in which all users and user-to-user influence strength both are topic-aware, is proposed.  ... 
doi:10.1109/access.2020.2978010 fatcat:dfuusfu6hbdr5bj3baoxhn7gmm

Online topic-aware influence maximization

Shuo Chen, Ju Fan, Guoliang Li, Jianhua Feng, Kian-lee Tan, Jinhui Tang
2015 Proceedings of the VLDB Endowment  
To address this problem, we study topic-aware influence maximization, which, given a topic-aware influence maximization (TIM) query, finds k seeds from a social network such that the topic-aware influence  ...  To efficiently find k seeds under the MIA model, we first propose a besteffort algorithm with 1 − 1 e approximation ratio, which estimates an upper bound of the topic-aware influence of each user and utilizes  ...  Topic-aware influence maximization under the MIA influence computation model is NP-hard. Proof.  ... 
doi:10.14778/2735703.2735706 fatcat:g2k2fnhunfemdcr74ko7ll3n5a


G Nandi .
2014 International Journal of Research in Engineering and Technology  
Online Social Network (OSN) mining has been a vast active area of research in the current years mainly due to the immense increase in the usage and popularity of such social networks.  ...  Hence this paper gives an idea about the hot topics related to OSN mining which will help the researchers to solve those challenges that still exist in mining OSNs.  ...  [31] , have considered influence propagation from the topics perspective. But in none of these papers a topic-wise influence model has been designed for generating influential users in OSNs.  ... 
doi:10.15623/ijret.2014.0304062 fatcat:6hjygspaengmhdrdxe3jaq436y

Discovering Temporal Retweeting Patterns for Social Media Marketing Campaigns

Guannan Liu, Yanjie Fu, Tong Xu, Hui Xiong, Guoqing Chen
2014 2014 IEEE International Conference on Data Mining  
By discovering the temporal retweeting patterns, we analyze the temporal popular topics and recommend tweets to users in a time-aware manner.  ...  Specifically, we investigate the users' retweeting patterns by modeling their retweeting behaviors as a generative process, which considers temporal, social, and topical factors.  ...  Some other work also exploited social influence in modeling documents generated in social network. Liu et al.  ... 
doi:10.1109/icdm.2014.48 dblp:conf/icdm/LiuFXXC14 fatcat:dws4pzv3ffc7djzywmrcjhglgu

Topic Propagation Prediction Based on Dynamic Probability Model

Jing Wang, Hui Zhao, Zhijing Liu
2019 IEEE Access  
INDEX TERMS Probability model, user role analysis, topic propagation prediction.  ...  Due to the unpredictability of the users and topics in social networks, predicting the topic propagation trend is still a major challenge. Different users play different roles in topic propagation.  ...  Users with strong social relationships and similar users can influence topic propagation. Second, based on user role analysis, we use dynamic probability model to predict topic propagation trend.  ... 
doi:10.1109/access.2019.2914479 fatcat:h2arq34bpnam7b777qtk5ljmha

Search Engine Drives the Evolution of Social Networks [article]

Cai Fu, Chenchen Peng, Xiao-Yang Liu
2017 arXiv   pre-print
Third, we quantitatively show that the search engine accelerates the rumor propagation in social networks.  ...  In this paper, we aim to quantitatively characterize the social network evolution phenomenon driven by a search engine. First, we propose a search network model for social network evolution.  ...  The experiment results show that the search engine has great influences on the characteristics of social networks and accelerates the rumor propagation significantly.  ... 
arXiv:1703.05922v1 fatcat:olfb3fahbja6raouxls4ng25jm
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