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Exploration of Social and Web Image Search Results Using Tensor Decomposition

Liuqing Yang, Evangelos E. Papalexakis
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
Empirically, social images on e.g., Twitter often tend to look more diverse and ultimately more "personal", contrary to images that are returned by web image search, some of which are so-called "stock"  ...  How do socially popular images differ from authoritative images indexed by web search engines?  ...  Papalexakis [1] served as inspiration for this paper.  ... 
doi:10.1109/cvprw.2017.239 dblp:conf/cvpr/YangP17 fatcat:yjvn52yr7rakhes7lnqwcugid4

Automatically Infer Human Traits and Behavior from Social Media Data [article]

Shimei Pan, Tao Ding
2018 arXiv   pre-print
People currently spend a significant amount of time on social media such as Twitter and Facebook.  ...  This makes social media a great source of large, rich and diverse human behavioral evidence.  ...  ., using graph analytics for social networks and natural language processing for text data), user data type will have significant impact on the machine learning algorithms employed.  ... 
arXiv:1804.04191v1 fatcat:y6j4haj6cfh2dbjpvmj6hxazc4

bBridge

Aleksandr Farseev, Ivan Samborskii, Tat-Seng Chua
2016 Proceedings of the 2016 ACM on Multimedia Conference - MM '16  
In this technical demonstration, we propose a cloud-based Big Data Platform for Social Multimedia Analytics called bBridge [9] that automatically detects and profiles meaningful user communities in a specified  ...  The system executes a community detection approach that considers the ability of social networks to complement each other during the process of latent representation learning, while the community profiling  ...  publish tweets that contain posts from other social networks (i.e. publish Instagram images on Twitter).  ... 
doi:10.1145/2964284.2973836 dblp:conf/mm/FarseevSC16 fatcat:qp5fusg3tnhgdat4llmiu5lq3a

Latent Dirichlet Allocation (LDA) and Topic modeling: models, applications, a survey [article]

Hamed Jelodar, Yongli Wang, Chi Yuan, Xia Feng, Xiahui Jiang, Yanchao Li, Liang Zhao
2018 arXiv   pre-print
There are various methods for topic modeling, which Latent Dirichlet allocation (LDA) is one of the most popular methods in this field.  ...  Topic modeling is one of the most powerful techniques in text mining for data mining, latent data discovery, and finding relationships among data, text documents.  ...  Acknowledgements This article has been awarded by the National Natural Science Foundation of China (61170035, 61272420, 81674099, 61502233), the Fundamental Research Fund for the Central Universities (  ... 
arXiv:1711.04305v2 fatcat:jzsx6owjyjfo3gkbohrc2ggkzq

Event detection and identification of influential spreaders in social media data streams

Leilei Shi, Yan Wu, Lu Liu, Xiang Sun, Liang Jiang
2018 Big Data Mining and Analytics  
Today Social Media plays an important role in our life. Some popular social media platform such as Facebook, Twitter etc. Using these we can be connected with each other.  ...  Traditional methods are not efficient for the detecting events and it requires more human intervention and having less accuracy.  ...  Social Media Data is open for through API.  ... 
doi:10.26599/bdma.2018.9020004 dblp:journals/bigdatama/ShiWLSJ18 fatcat:kqajnoxyfra43anj3v2dj767oe

"360° user profiling: past, future, and applications" by Aleksandr Farseev, Mohammad Akbari, Ivan Samborskii and Tat-Seng Chua with Martin Vesely as coordinator

Aleksandr Farseev, Mohammad Akbari, Ivan Samborskii, Tat-Seng Chua
2016 ACM SIGWEB Newsletter  
We explain the weakness and strength of these methods and introduce an analytic platform to bridge the gap between social media users, business intelligence and the Big Data.  ...  These profiles and groups are often used as a basis for rendering better online services, marketing, and advertisement.  ...  when users publish tweets that contain posts from other social networks (i.e. post Instagram images on Twitter).  ... 
doi:10.1145/2956573.2956577 fatcat:l6eaj76gvnahdkw7wlrhmtiohi

Social Tagging System for Community Detecting using NLP Technique

Mrs. C. Gomathi
2018 International Journal for Research in Applied Science and Engineering Technology  
The tags and latent interactions among users are incorporated in the method In our experiments, the social dynamic behaviors of users are first analyzed in face book and twitter datasets.  ...  Social tagging systems for community detecting in social networks, users usually have different intentions when tagging.  ...  In social networks, community detection is important for other studies, such as opinion mining and personalized information retrieval.  ... 
doi:10.22214/ijraset.2018.4279 fatcat:qldlijoa2rb2jmgty44hjh4sum

Digital Memory in the Post-Witness Era: How Holocaust Museums Use Social Media as New Memory Ecologies

Stefania Manca
2021 Information  
A mixed-method approach based on a combination of social media analytics and latent semantic analysis was used to investigate the Facebook, Twitter, Instagram, and YouTube profiles of Yad Vashem, the United  ...  Overall, the results show that the three organisations are more active on Twitter than on Facebook and Instagram, with the Auschwitz–Birkenau Museum and Memorial occupying a prominent position in Twitter  ...  Acknowledgments: This study was carried out as part of the author's research project "Teaching and learning about the Holocaust with social media: A learning ecologies perspective"-Doctoral programme in  ... 
doi:10.3390/info12010031 fatcat:3ou4pzwawfbnbfiq7m7by66zzm

Discovering the City by Mining Diverse and Multimodal Data Streams

Yin-Hsi Kuo, Chung-Yen Hung, Liang-Chi Hsieh, Winston Hsu, Yan-Ying Chen, Bor-Chun Chen, Wen-Yu Lee, Chun-Che Wu, Chia-Hung Lin, Yu-Lin Hou, Wen-Feng Cheng, Yi-Chih Tsai
2014 Proceedings of the ACM International Conference on Multimedia - MM '14  
For example, Instagram users share more food and travel photos while Twitter users discuss more about sports and news.  ...  Because different social media are usually chosen for specific purposes, multiple social media mining and integration are essential to understand a city comprehensively.  ...  Our contributions include, 1) leveraging the complementary information for data analytics, 2) discovering the latent behaviors, synergies and differences among media sources, 3) mining effective factors  ... 
doi:10.1145/2647868.2656406 dblp:conf/mm/KuoCCLWLHCTHHH14 fatcat:z44e4ticmjaldnynjylc6k6vii

Spatiotemporal social media analytics for abnormal event detection and examination using seasonal-trend decomposition

Junghoon Chae, Dennis Thom, Harald Bosch, Yun Jang, Ross Maciejewski, David S. Ebert, Thomas Ertl
2012 2012 IEEE Conference on Visual Analytics Science and Technology (VAST)  
topics and events within various social media data sources, such as Twitter, Flickr and YouTube.  ...  Figure 1 : Social media analysis system including message plots on a map, abnormality estimation charts and tables for message content and topic exploration.  ...  We would like to thank the reviewers for their valuable suggestions and comments, which helped to improve the presentation of this work.  ... 
doi:10.1109/vast.2012.6400557 dblp:conf/ieeevast/ChaeTBJMEE12 fatcat:gevduox26fdddipfh5go3dqexa

Uncovering Latent Mobility Patterns from Twitter During Mass Events

Enrico Steiger, Timothy Ellersiek, Bernd Resch, Alexander Zipf
2015 GI_FORUM - Journal for Geographic Information Science  
The investigation of human activity in location-based social networks such as Twitter is one promising example of exploring spatial structures in order to infer underlying mobility patterns.  ...  Previous work regarding Twitter analysis is mainly focused on the spatiotemporal classification of events.  ...  We also thank the existing social network community of Twitter for providing access to free available social media data.  ... 
doi:10.1553/giscience2015s525 fatcat:mzrutrrjrbcnlfd56hfa7bl4km

Detailed Technical Programme Schedule

2020 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)  
in Social Internet of Things Session-12.01: E-Healthcaredata Analytics and Security Session Chair(s): Dr.Aman Sharma, Jaypee University of Information Technology, Waknaghat Date: 7th November, 2020 Time  ...  University of Information Technology, Waknaghat Paper Title Machine Learning Technique for Wireless Sensor Networks Novel Machine Learning Approach for Sentiment Analysis of Real Time Twitter Data with  ... 
doi:10.1109/pdgc50313.2020.9315322 fatcat:4ndwytytovb7xkntz7bmaurj6a

Mining Cross-network Association for YouTube Video Promotion

Ming Yan, Jitao Sang, Changsheng Xu
2014 Proceedings of the ACM International Conference on Multimedia - MM '14  
Based on the proposed framework, we also discuss the potential applications, extensions, and suggest some principles for future heterogeneous social media utilization and cross-network collaborative applications  ...  We introduce a novel cross-network collaborative problem in this work: given YouTube videos, to find optimal Twitter followees that can maximize the video promotion on Twitter.  ...  Corr-LDA is proposed for the problem of image annotation, by modeling the correspondence between image segments and caption words.  ... 
doi:10.1145/2647868.2654920 dblp:conf/mm/YanSX14 fatcat:52vik2zrtfcvtpaenhy4vjn6kq

Social Media-based User Embedding: A Literature Review

Shimei Pan, Tao Ding
2019 Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence  
The technology is critical for creating high performance social media-based human traits and behavior models since the ground truth for assessing latent human traits and behavior is often expensive to  ...  In this survey, we review typical methods for learning a unified user embeddings from heterogeneous user data (e.g., combines social media texts with images to learn a unified user representation).  ...  as the images shared on social media; social network refers to social connections between different user accounts such as the friendship network on Facebook and the follower/retweet network on Twitter.  ... 
doi:10.24963/ijcai.2019/881 dblp:conf/ijcai/PanD19 fatcat:inw55rewvzh5nckevzvrsexwii

The Impact of Social Network Media on Brand Equity in SMEs

2015 European Journal of Sustainable Development  
Key words: social network; word of mouth marketing; consumer behavior; brand equity, Social network-facebook-EWOM-brand awareness-brand image-consumer attitude-consumer behavior, SMEs European Journal  ...  In this term social network media play a considerable role in peoples' daily lives and business by information sharing and the impressions of friends' comments on own view.  ...  Based on netnographic, sociology literature and marketing literature on social network analysis, a common friend in a social network becomesan effective medium of information dispersion.  ... 
doi:10.14207/ejsd.2016.v5n3p239 fatcat:dpptlzqjqncp7hcgbda5i2n42q
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