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social-networking--online
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A comprehensive analysis of twitter trending topics
, Article 5th International Conference on Web Research, ICWR 2019, 24 April 2019 through 25 April 2019 ; 2019 , Pages 22-27 ; 9781728114316 (ISBN) ; Habibi, J ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
Twitter is among the most used microblogging and online social networking services. In Twitter, a name, phrase, or topic that is mentioned at a greater rate than others is called a «trending topic» or simply «trend». Twitter trends has shown their powerful ability in many public events, elections and market changes. Nevertheless, there has been very few works focusing on understanding the dynamics of these trending topics. In this article, we thoroughly examined the Twitter's trending topics of 2018. To this end, we accessed Twitter's trends API for the full year of 2018, and devised six criteria to evaluate our dataset. These six criteria are: lexical analysis, time to reach, trend...
Observations on failure in blogs
, Article 2007 International Conference on Weblogs and Social Media, ICWSM 2007, Boulder, CO, 26 March 2007 through 28 March 2007 ; 2007 ; Rassoulian, A ; Adibi, J ; Sharif University of Technology
2007
Abstract
The capability of placing "comments" on the posts makes the blogspaces rather a complex environment. One of the interesting phenomena in blogspace is "blogger failure" when a blogger stops writing after a certain amount of time and will not return to blogspace for a long time, or when a blogger does not get any comment from her audience. In this paper we illustrate our observation on bloggers failure in a unique blogspace. First, we introduce PersianBlog blogspace briefly along with our observations of behaviors of bloggers on placing comments. Next, we will provide our definition of failure, and give a broad future research path to model failure in blogspace
A matrix factorization model for hellinger-based trust management in social internet of things
, Article IEEE Transactions on Dependable and Secure Computing ; 2021 ; 15455971 (ISSN) ; Mahyar, H ; Movaghar, A ; Stanley, H. E ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2021
Abstract
The Social Internet of Things (SIoT), integration of the Internet of Things and Social Networks paradigms, has been introduced to build a network of smart nodes that are capable of establishing social links. In order to deal with misbehaving service provider nodes, service requestor nodes must evaluate their trustworthiness levels. In this paper, we propose a novel trust management mechanism in the SIoT to predict the most reliable service providers for each service requestor, which leads to reduce the risk of being exposed to malicious nodes. We model the SIoT with a flexible bipartite graph, then build a social network among the service requestor nodes, using the Hellinger distance....
Social power and opinion formation in complex networks
, Article Physica A: Statistical Mechanics and its Applications ; Volume 392, Issue 4 , 2013 , Pages 959-966 ; 03784371 (ISSN) ; Sharif University of Technology
2013
Abstract
In this paper we investigate the effects of social power on the evolution of opinions in model networks as well as in a number of real social networks. A continuous opinion formation model is considered and the analysis is performed through numerical simulation. Social power is given to a proportion of agents selected either randomly or based on their degrees. As artificial network structures, we consider scale-free networks constructed through preferential attachment and Watts-Strogatz networks. Numerical simulations show that scale-free networks with degree-based social power on the hub nodes have an optimal case where the largest number of the nodes reaches a consensus. However, given...
Characterizing twitter with respondent-driven sampling
, Article Proceedings - IEEE 9th International Conference on Dependable, Autonomic and Secure Computing, DASC 2011, 12 December 2011 through 14 December 2011, Sydney, NSW ; 2011 , Pages 1211-1217 ; 9780769546124 (ISBN) ; Rabiee, H. R ; Nabavi, N ; Pooya, S ; Sharif University of Technology
2011
Abstract
Twitter as one of the most important microblogging online social networks has attracted more than 200 million users in recent years. Although there have been several attempts on characterizing the Twitter by using incomplete sampled data, they have not been very successful to estimate the characteristics of the whole network. In this paper, we characterize Twitter by sampling from its social graph and user behaviors through a random walk based sampling technique called Respondent-Driven Sampling (RDS). To the best of our knowledge, for the first time RDS method and its estimator are used in order to obtain uniform unbiased estimation of several key structural and behavioral properties of...
Online conflict-free coloring of intervals
, Article Scientia Iranica ; Vol. 21, issue. 6 , 2014 , p. 2138-2141 ; Seraji, M. J. R ; Shadravan, M ; Sharif University of Technology
Abstract
In this paper, we study the problem of online conflict-free coloring of intervals on a line, where each newly inserted interval must be assigned a color upon insertion such that the coloring remains conflict-free, i.e. for each point p in the union of the current intervals, there must be an interval I with a unique color among all intervals covering p. We first present a simple algorithm which uses O(√n) colors where n is the number of current intervals. Next, we propose an CF-coloring of intervals which uses O(log3 n) colors
Community structure and information cascade in signed networks
, Article New Generation Computing ; Vol. 32, issue. 3-4 , August , 2014 , p. 257-269 ; Jalili, M ; Sharif University of Technology
Abstract
In this paper, we study information cascade in networks with positive and negative edges. The cascade depth is correlated with community structure of signed networks where communities are defined such that positive inter-community and negative intra-community links are minimized. The cascade is initialized from a number of nodes that are selected randomly. Finally, the number of nodes that have participated in the cascade is interpreted as cascade depth; the more the number of such nodes, the more the depth of the cascade. We investigate influence of community structure (i.e.; percentage of inter-community positive and intra-community negative links) on the cascade depth. We find significant...
Pricing in population games with semi-rational agents
, Article Operations Research Letters ; Volume 41, Issue 3 , 2013 , Pages 226-231 ; 01676377 (ISSN) ; Ghodsi, M ; Mahini, H ; Safari, M. A ; Sharif University of Technology
2013
Abstract
We consider a market in which two competing sellers offer two similar products on a social network. In this market, each agent chooses iteratively between the products based on her neighbors reactions and prices. This introduces two games: one between the agents and one between the sellers. We show that the first game is a full potential game and provide an algorithm to compute its convergence point. We also study various properties of the second game such as its equilibrium points and convergence
A joint classification method to integrate scientific and social networks
, Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; Volume 7814 LNCS , March , 2013 , Pages 122-133 ; 03029743 (ISSN) ; 9783642369728 (ISBN) ; Asgari, E ; Hiemstra, D ; Beigy, H ; Sharif University of Technology
2013
Abstract
In this paper, we address the problem of scientific-social network integration to find a matching relationship between members of these networks. Utilizing several name similarity patterns and contextual properties of these networks, we design a focused crawler to find high probable matching pairs, then the problem of name disambiguation is reduced to predict the label of each candidate pair as either true or false matching. By defining matching dependency graph, we propose a joint label prediction model to determine the label of all candidate pairs simultaneously. An extensive set of experiments have been conducted on six test collections obtained from the DBLP and the Twitter networks to...
Naturality of network creation games, measurement and analysis
, Article Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 ; 2012 , Pages 716-717 ; 9780769547992 (ISBN) ; Fahmi, Z ; Fazli, M ; Habibi, J ; Jalaly, P ; Safari, M ; Sharif University of Technology
2012
Abstract
Modeling is one of the major research areas in social network analysis whose goal is to study networks structure and its evolution. Motivated by the intuition that members in social networks behave selfishly, network creation games have been introduced for modeling social networks. In this paper, our aim is to measure how much the output graphs of a given network creation game are compatible with a social network. We first show that the precise measurement is not possible in polynomial time. Then we propose a method for its approximation; finally, we show the usability of our method by conducting experiments on real network data
An inspection game to provide incentive for cooperation with corrupted inspectors
, Article Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012 ; 2012 , Pages 730-732 ; 9780769547992 (ISBN) ; Safari, M. A ; Sharif University of Technology
2012
Abstract
Open and autonomous environments, such as peer to peer networks or many social networks, are efficient only if cooperation among nodes is ensured. In order to ensure cooperative behavior, we have added a new node type to the system, called inspector and used game theoretical tools to analyze the system. Inspectors punish both misbehaving nodes as well as nodes who provide dishonest ratings about other peers. Analyzing the proposed inspection game ensures that corruption of inspectors and misbehavior of nodes is bounded. The game enables the system designer to set the amount of corruption that is allowed according to the budget
Local model of a scientific collaboration in physics network compared with the global model
, Article Physica A: Statistical Mechanics and its Applications ; Volume 389, Issue 23 , 2010 , Pages 5530-5537 ; 03784371 (ISSN) ; Shirazi, A. H ; Kargaran, A ; Jafari, G. R ; Sharif University of Technology
2010
Abstract
We have constructed a collaboration network for physicists based in Iran working in different disciplines. By discussing properties like collaborators per author, shortest path, betweenness, and the concept of power in networks for this local model, and comparing with the global model, we understand how a developing country in the Middle East is contributing to the scientific growth in the world statistically. In this comparison, we found some properties of the local model which were not in accordance with the standard global society of science, which should be considered in developing the future policies. Our results show significant differences in factors like the degree and the diameter...
HNP3: A hierarchical nonparametric point process for modeling content diffusion over social media
, Article 16th IEEE International Conference on Data Mining, ICDM 2016, 12 December 2016 through 15 December 2016 ; 2017 , Pages 943-948 ; 15504786 (ISSN); 9781509054725 (ISBN) ; Khodadadi, A ; Arabzadeh, A ; Rabiee, H. R ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2017
Abstract
This paper introduces a novel framework for modeling temporal events with complex longitudinal dependency that are generated by dependent sources. This framework takes advantage of multidimensional point processes for modeling time of events. The intensity function of the proposed process is a mixture of intensities, and its complexity grows with the complexity of temporal patterns of data. Moreover, it utilizes a hierarchical dependent nonparametric approach to model marks of events. These capabilities allow the proposed model to adapt its temporal and topical complexity according to the complexity of data, which makes it a suitable candidate for real world scenarios. An online inference...
A novel granular approach for detecting dynamic online communities in social network
, Article Soft Computing ; 2018 ; 14327643 (ISSN) ; Zakerolhosseini, A ; Bagheri Shouraki, S ; Homayounvala, E ; Sharif University of Technology
Springer Verlag
2018
Abstract
The great surge in the research of community discovery in complex network is going on due to its challenging aspects. Dynamicity and overlapping nature are among the common characteristics of these networks which are the main focus of this paper. In this research, we attempt to approximate the granular human-inspired viewpoints of the networks. This is especially helpful when making decisions with partial knowledge. In line with the principle of granular computing, in which precision is avoided, we define the micro- and macrogranules in two levels of nodes and communities, respectively. The proposed algorithm takes microgranules as input and outputs meaningful communities in rough...
Compressed sensing in cyber physical social systems
, Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; Volume 10760 LNCS , 2018 , Pages 287-305 ; 03029743 (ISSN) ; Ghalebi, K. E ; Movaghar, A ; Mahyar, H ; Sharif University of Technology
Abstract
We overview the main results in Compressed Sensing and Social Networks, and discuss the impact they have on Cyber Physical Social Systems (CPSS), which are currently emerging on top of the Internet of Things. Moreover, inspired by randomized Gossip Protocols, we introduce TopGossip, a new compressed-sensing algorithm for the prediction of the top-k most influential nodes in a social network. TopGossip is able to make this prediction by sampling only a relatively small portion of the social network, and without having any prior knowledge of the network structure itself, except for its set of nodes. Our experimental results on three well-known benchmarks, Facebook, Twitter, and Barabási,...
A technique to improve De-anonymization attacks on graph data
, Article 26th Iranian Conference on Electrical Engineering, ICEE 2018, 8 May 2018 through 10 May 2018 ; 2018 , Pages 704-709 ; 9781538649169 (ISBN) ; Delavar, M ; Mohajeri, J ; Salmasizadeh, M ; Sharif University of Technology
Abstract
Social networks and the shared data in these networks are always considered as good opportunities in hands of the attackers. To evaluate the privacy risks in these networks and challenge the anonymization techniques, several de-anonymization attacks have been introduced so far. In this paper, we propose a technique to improve the success rate of passive seed based de-anonymization attacks. Our proposed technique is simple and can be applied in combination with different types of de-anonymization attacks. We show that it can achieve high success rates with low number of seeds compared to similar attacks. Our technique can also be used for applying partial attacks on graphs which results in...
Community detection using diffusion information
, Article ACM Transactions on Knowledge Discovery from Data ; Volume 12, Issue 2 , 2018 ; 15564681 (ISSN) ; Khodadadi, A ; Rabiee, H. R ; Sharif University of Technology
Association for Computing Machinery
2018
Abstract
Community detection in social networks has become a popular topic of research during the last decade. There exist a variety of algorithms for modularizing the network graph into different communities. However, they mostly assume that partial or complete information of the network graphs are available that is not feasible in many cases. In this article, we focus on detecting communities by exploiting their diffusion information. To this end, we utilize the Conditional Random Fields (CRF) to discover the community structures. The proposed method, community diffusion (CoDi), does not require any prior knowledge about the network structure or specific properties of communities. Furthermore, in...
Cross-cultural studies using social networks data
, Article IEEE Transactions on Computational Social Systems ; Volume 6, Issue 4 , 2019 , Pages 627-636 ; 2329924X (ISSN) ; Fazli, M ; Habibi, J ; Tavakoli, S ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
With the widespread access of people to the Internet and the increasing usage of social networks in all nations, social networks have become a new source to study cultural similarities and differences. We identified major issues in traditional methods of data collection in cross-cultural studies: Difficulty in access to people from many nations, limited number of samples, negative effects of translation, positive self-enhancement illusion, and a few unreported problems. These issues are either causing difficulty to perform a cross-cultural study or have negative impacts on the validity of the final results. In this paper, we propose a framework that aims to calculate cultural distance among...
Centrality-based group formation in group recommender systems
, Article 26th International World Wide Web Conference, WWW 2017 Companion, 3 April 2017 through 7 April 2017 ; 2019 , Pages 1187-1196 ; 9781450349147 (ISBN) ; Khalili, S ; Elahe Ghalebi, K ; Grosu, R ; Mojde Morshedi, S ; Movaghar, A ; Sharif University of Technology
International World Wide Web Conferences Steering Committee
2019
Abstract
Recommender Systems have become an attractive field within the recent decade because they facilitate users' selection process within limited time. Conventional recommender systems have proposed numerous methods focusing on recommendations to individual users. Recently, due to a significant increase in the number of users, studies in this field have shifted to properly identify groups of people with similar preferences and provide a list of recommendations for each group. Offering a recommendations list to each individual requires significant computational cost and it is therefore often not efficient. So far, most of the studies impose four restrictive assumptions: (1) limited number of...
Applying and inferring fuzzy trust in Semantic Web social networks
, Article 1st Canadian Semantic Web Working Symposium, CSWWS 2006, Quebec City, QC, 6 June 2006 through 6 June 2006 ; 2006 , Pages 23-43 ; 9780387298153 (ISBN) ; Bagheri, S ; Sharif University of Technology
Kluwer Academic Publishers
2006
Abstract
Social networks let the people find and know other people and benefit form their information. Semantic Web standard ontologies support social network sites for making use of other social networks information and hence help their expansion and unification, making them a huge social network. As social networks are public virtual social places much information may exist in them that may not be trustworthy to all. A mechanism in needed to rate coming news, reviews and opinions about a definite subject from users, according to each user preference. There should be a feature for users to specify how much they trust a friend and a mechanism to infer the trust from one user to another that is not...