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Social Network Analysis and Mining, Volume 9
Volume 9, Number 1, December 2019
- Mohammed Bekkali
, Abdelmonaime Lachkar:
An effective short text conceptualization based on new short text similarity. 1:1-1:11 - Yayati Gupta, S. R. S. Iyengar, Akrati Saxena
Modeling memetics using edge diversity. 2:1-2:17 - Akrati Saxena
A heuristic approach to estimate nodes' closeness rank using the properties of real world networks. 3:1-3:16 - Loris Belcastro
ParSoDA: high-level parallel programming for social data mining. 4:1-4:19 - Jyoti Sunil More, Chelpa Lingam:
A gradient-based methodology for optimizing time for influence diffusion in social networks. 5:1-5:10 - George A. Barnett, Carlos Algara
Diachronic equivalence: an examination of the international news network. 6:1-6:11 - Ashkan Ebadi
A quest for the structure of intra- and postoperative surgical team networks: does the small-world property evolve over time? 7:1-7:20 - Tjeerd Zandberg
Missing behavior data in longitudinal network studies: the impact of treatment methods on estimated effect parameters in stochastic actor oriented models. 8:1-8:20 - Mehjabin Khatoon
An efficient method to detect communities in social networks using DBSCAN algorithm. 9:1-9:12 - Francesca Spezzano
Detecting pages to protect in Wikipedia across multiple languages. 10:1-10:16 - Arif Mohaimin Sadri
Joint inference of user community and interest patterns in social interaction networks. 11:1-11:23 - Monika Arora
Character level embedding with deep convolutional neural network for text normalization of unstructured data for Twitter sentiment analysis. 12:1-12:14 - Keshab Nath
Detecting intrinsic communities in evolving networks. 13:1-13:15 - Soumajyoti Sarkar
Using network motifs to characterize temporal network evolution leading to diffusion inhibition. 14:1-14:24 - Ruggero G. Pensa
Network-aware privacy risk estimation in online social networks. 15:1-15:15 - Mohan Timilsina
Heat diffusion approach for scientific impact analysis in social media. 16:1-16:13 - Laxmi Amulya Gundala, Francesca Spezzano
Estimating node indirect interaction duration to enhance link prediction. 17:1-17:13 - Shreekanth M. Prabhu, Balasubramanya Murthy Kannanedhi Narasimha Sastry, Natarajan Subramanyam:
Validating Tantra Framework using entropy. 18:1-18:18 - Anas Aloudat
Why some people do not use Facebook? 19:1-19:14 - T. M. G. Tennakoon
FCMiner: mining functional communities in social networks. 20:1-20:19 - Ali Vardasbi
Solving submodular text processing problems using influence graphs. 21:1-21:15 - Soheil Jamshidi
Characterizing the dynamics and evolution of incentivized online reviews on Amazon. 22:1-22:15 - Mehdi Azaouzi
Community detection in large-scale social networks: state-of-the-art and future directions. 23:1-23:32 - Biraj Dahal, Sathish A. P. Kumar
Topic modeling and sentiment analysis of global climate change tweets. 24:1-24:20 - Aqsa Mehreen, Yang Hui, Ali Zulqurnain
A social network theory perspective on how social ties influence perceived employability and job insecurity: evidence from school teachers. 25:1-25:17 - Allan Fong
Using medication administration and double-check data to infer social network influence in intensive care units. 26:1-26:8 - Tao Ding
Predicting delay discounting from heterogeneous social media data. 27:1-27:15 - Dharavath Ramesh
Spark's GraphX-based link prediction for social communication using triangle counting. 28:1-28:12 - Jürgen Lerner
Team diversity, polarization, and productivity in online peer production. 29:1-29:17 - Hugo Hromic
Characterising and evaluating dynamic online communities from live microblogging user interactions. 30:1-30:18 - Adam Badawy, Aseel Addawood, Kristina Lerman, Emilio Ferrara
Characterizing the 2016 Russian IRA influence campaign. 31:1-31:11 - Steven E. Massey:
Form and relationship of the social networks of the New Testament. 32:1-32:13 - Ali Hashemi, Mohammad Ali Zare Chahooki
Telegram group quality measurement by user behavior analysis. 33:1-33:12 - Raazesh Sainudiin
Characterizing the Twitter network of prominent politicians and SPLC-defined hate groups in the 2016 US presidential election. 34:1-34:15 - Oguzhan Çitlak
A survey on detecting spam accounts on Twitter network. 35:1-35:13 - Derek Doran, Luisa Massari
User interactions and behaviors in a large-scale online emotional support service. 36:1-36:22 - Liqiang Wang
Understanding archetypes of fake news via fine-grained classification. 37:1-37:17 - Ajitesh Srivastava
Network-based intervention strategies to reduce violence among homeless. 38:1-38:12 - Panagiotis Symeonidis, Stergios Chairistanidis:
OmniRank: learning to recommend based on omni-traversal of heterogeneous graphs. 39:1-39:13 - Bhawna Saxena
A node activity and connectivity-based model for influence maximization in social networks. 40:1-40:16 - Nuha Albadi
Investigating the effect of combining GRU neural networks with handcrafted features for religious hatred detection on Arabic Twitter space. 41:1-41:19 - Madichetty Sreenivasulu
Disaster damage assessment from the tweets using the combination of statistical features and informative words. 42:1-42:11 - Imane Khaouja
Building a soft skill taxonomy from job openings. 43:1-43:19 - Xukun Li, Doina Caragea
Localizing and quantifying infrastructure damage using class activation mapping approaches. 44:1-44:15 - Zakariya Ghalmane, Mohammed El Hassouni, Hocine Cherifi
Immunization of networks with non-overlapping community structure. 45:1-45:22 - Matteo Francia
Social BI to understand the debate on vaccines on the Web and social media: unraveling the anti-, free, and pro-vax communities in Italy. 46:1-46:16 - Mohammad Hajarian
A personalized gamification method for increasing user engagement in social networks. 47:1-47:14 - Bahareh Ashenagar, Ali Hamzeh
Forming a well-connected team of experts based on a social network graph: a novel weighting approach. 48:1-48:20 - Didier Grimaldi
Can we analyse political discourse using Twitter? Evidence from Spanish 2019 presidential election. 49:1-49:9 - Ammara Habib, Muhammad Zubair Asghar
False information detection in online content and its role in decision making: a systematic literature review. 50:1-50:20 - Ryan A. Rossi, Nesreen K. Ahmed
Complex networks are structurally distinguishable by domain. 51:1-51:13 - Ammar Mohammed
Deep learning approaches for Arabic sentiment analysis. 52:1-52:12 - Hugo Hromic
Correction to: Characterising and evaluating dynamic online communities from live microblogging user interactions. 53:1 - Jenny Jin, Guigang Zhang, Phillip C.-Y. Sheu
Influence maximization in graph-based OLAP (GOLAP). 54:1-54:26 - Abdelmalek Habi
Diversified top-k search with relaxed graph simulation. 55:1-55:15 - Imane Guellil
Arabic sentiment analysis: studies, resources, and tools. 56:1-56:17 - Soumajyoti Sarkar
Mining user interaction patterns in the darkweb to predict enterprise cyber incidents. 57:1-57:28 - Chainarong Amornbunchornvej
Mining and modeling complex leadership-followership dynamics of movement data. 58:1-58:17 - Taleb Khafaei
Tracing temporal communities and event prediction in dynamic social networks. 59:1-59:11 - Zachary K. Stine, Nitin Agarwal:
Characterizing the language-production dynamics of social media users. 60:1-60:13 - Karsten Ladner, Ruchishya Ramineni, K. M. George
Activeness of Syrian refugee crisis: an analysis of tweets. 61:1-61:16 - Mikel Joaristi, Edoardo Serra
Detecting suspicious entities in Offshore Leaks networks. 62:1-62:15 - Gabriel Barina
Agent-based simulations of payoff distribution in economic networks. 63:1-63:18 - Dionisis Margaris
Handling uncertainty in social media textual information for improving venue recommendation formulation quality in social networks. 64:1-64:19 - Roberto Interdonato
A lightweight and multilingual framework for crisis information extraction from Twitter data. 65:1-65:20 - Yunlei Zhang, Dingyi Yin, Bin Wu, Feiyu Long, Yinchang Cui, Xun Bian:
PLinkSHRINK: a parallel overlapping community detection algorithm with Link-Graph for large networks. 66:1-66:17
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