New trends and applications in social media analytics

Abstract The fast growth of social media platforms and their related applications have dramatically changed the way billions of people relate to each other on the Web. This evolution of social media has blossomed in a plethora of end-user, or user-centered, applications that required innovative and efficient techniques for data processing. This was made possible recently thanks to advances in data science and artificial intelligence in fields like pattern recognition, information fusion, knowledge discovery and data visualization. This special issue provides a set of 12 selected papers (out of 65 submissions) that represent latest advances and developments in these areas.

[1]  Sancho Salcedo-Sanz,et al.  A Multi-Objective Genetic Algorithm for overlapping community detection based on edge encoding , 2018, Inf. Sci..

[2]  Barbara Poblete,et al.  Social QA in non-CQA platforms , 2020, Future Gener. Comput. Syst..

[3]  André L. L. de Aquino,et al.  An evolutionary algorithm for roadside unit deployment with betweenness centrality preprocessing , 2018, Future Gener. Comput. Syst..

[4]  Mimoun Malki,et al.  Composing WoT services with uncertain data , 2019, Future Gener. Comput. Syst..

[5]  Erik Cambria,et al.  The Four Dimensions of Social Network Analysis: An Overview of Research Methods, Applications, and Software Tools , 2020, Inf. Fusion.

[6]  Francisco Herrera,et al.  What do people think about this monument? Understanding negative reviews via deep learning, clustering and descriptive rules , 2020, J. Ambient Intell. Humaniz. Comput..

[7]  Erik Cambria,et al.  A review of sentiment analysis research in Arabic language , 2020, Future Gener. Comput. Syst..

[8]  Philip C. Treleaven,et al.  Social media analytics: a survey of techniques, tools and platforms , 2014, AI & SOCIETY.

[9]  Kevin Chen-Chuan Chang,et al.  Embedding Both Finite and Infinite Communities on Graphs [Application Notes] , 2019, IEEE Comput. Intell. Mag..

[10]  Erik Cambria,et al.  Word Polarity Disambiguation Using Bayesian Model and Opinion-Level Features , 2014, Cognitive Computation.

[11]  Francisco Herrera,et al.  Sentiment Analysis in TripAdvisor , 2017, IEEE Intelligent Systems.

[12]  Julio César Hernández Castro,et al.  Detecting discussion communities on vaccination in twitter , 2017, Future Gener. Comput. Syst..

[13]  Francisco Herrera,et al.  Inconsistencies on TripAdvisor reviews: A unified index between users and Sentiment Analysis Methods , 2019, Neurocomputing.

[14]  Carmen Zarco,et al.  Marketing analysis of wineries using social collective behavior from users' temporal activity on Twitter , 2020, Inf. Process. Manag..

[15]  David Camacho,et al.  Adaptive k-Means Algorithm for Overlapped Graph Clustering , 2012, Int. J. Neural Syst..

[16]  Stefan Stieglitz,et al.  Social Media Analytics , 2014, Business & Information Systems Engineering.

[17]  Erik Cambria,et al.  Extracting Time Expressions and Named Entities with Constituent-Based Tagging Schemes , 2020, Cognitive Computation.

[18]  Erik Cambria,et al.  Semi-supervised learning for big social data analysis , 2018, Neurocomputing.

[19]  Erik Cambria,et al.  Sentic Computing for social media marketing , 2012, Multimedia Tools and Applications.

[20]  Siu-Ming Yiu,et al.  Incentive evolutionary game model for opportunistic social networks , 2020, Future Gener. Comput. Syst..

[21]  Erik Cambria,et al.  Sentic Medoids: Organizing Affective Common Sense Knowledge in a Multi-Dimensional Vector Space , 2011, ISNN.

[22]  Francisco Herrera,et al.  Distinguishing between facts and opinions for sentiment analysis: Survey and challenges , 2018, Inf. Fusion.

[23]  Anália Lourenço,et al.  Understanding the social evolution of the Java community in Stack Overflow: A 10-year study of developer interactions , 2020, Future Gener. Comput. Syst..

[24]  Erik Cambria,et al.  Natural language based financial forecasting: a survey , 2017, Artificial Intelligence Review.

[25]  Luis Alfonso Ureña López,et al.  Improved emotion recognition in Spanish social media through incorporation of lexical knowledge , 2020, Future Gener. Comput. Syst..

[26]  Erik Cambria,et al.  Sentic LSTM: a Hybrid Network for Targeted Aspect-Based Sentiment Analysis , 2018, Cognitive Computation.

[27]  Gonzalo A. Ruz,et al.  Sentiment analysis of Twitter data during critical events through Bayesian networks classifiers , 2020, Future Gener. Comput. Syst..

[28]  David Camacho,et al.  Describing Alt-Right communities and their discourse on Twitter during the 2018 US mid-term elections , 2019, COMPLEX NETWORKS.

[29]  Jason J. Jung,et al.  Social big data: Recent achievements and new challenges , 2015, Information Fusion.

[30]  Miguel Molina-Solana,et al.  Towards a large-scale twitter observatory for political events , 2020, Future Gener. Comput. Syst..

[31]  Jane Yung-jen Hsu,et al.  Sentic blending: Scalable multimodal fusion for the continuous interpretation of semantics and sentics , 2013, 2013 IEEE Symposium on Computational Intelligence for Human-like Intelligence (CIHLI).

[32]  Javier Del Ser,et al.  Let nature decide its nature: On the design of collaborative hyperheuristics for decentralized ephemeral environments , 2018, Future Gener. Comput. Syst..

[33]  Hoang Long Nguyen,et al.  Social event decomposition for constructing knowledge graph , 2019, Future Gener. Comput. Syst..

[34]  Sandeep K. Sood,et al.  Fog-cloud based cyber-physical system for distinguishing, detecting and preventing mosquito borne diseases , 2018, Future Gener. Comput. Syst..