Beyond streams and graphs: dynamic tensor analysis
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Structural and temporal analysis of the blogosphere through community factorization
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Blog Community Discovery and Evolution Based on Mutual Awareness Expansion
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Contextualising tags in collaborative tagging systems
Proceedings of the 20th ACM conference on Hypertext and hypermedia
Incremental spectral clustering by efficiently updating the eigen-system
Pattern Recognition
Temporal and information flow based event detection from social text streams
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Community mining on dynamic weighted directed graphs
Proceedings of the 1st ACM international workshop on Complex networks meet information & knowledge management
Clustering of Social Tagging System Users: A Topic and Time Based Approach
WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
Handbook of Natural Language Processing
Handbook of Natural Language Processing
Characterizing debate performance via aggregated twitter sentiment
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Emotional aware clustering on micro-blogging sources
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
Ontologies are us: a unified model of social networks and semantics
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Social networking trends and dynamics detection via a cloud-based framework design
Proceedings of the 21st international conference companion on World Wide Web
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Social networks drive todays opinions and content diffusion. Large scale, distributed and unpredictable social data streams are produced and such evolving data production offers the ground for the data mining and analysis tasks. Such social data streams embed human reactions and inter-relationships and affective and emotional analysis has become rather important in todays applications. This work highlights the major data structures and methodologies used in evolving social data mining and proceeds to the relevant affective analysis techniques. A particular framework is outlined along with indicative applications which employ evolving social data analysis with emphasis on the seminal criteria of topic, location and time. Such mining and analysis overview is beneficial for various scientific and enterpreneural audiences and communities in the social networking area.