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Online Social Networks Event Detection: A Survey [chapter]

Mário Cordeiro, João Gama
2016 Lecture Notes in Computer Science  
Performing event detection on online social networks is no exception, state-of-the-art algorithms rely on text mining techniques applied to pre-known datasets that are being processed with no restrictions  ...  This specific problem of event detection becomes even more serious due to the real-time nature of online social networks.  ...  Modern event detection systems face important challenges when dealing with the high-volume, unbounded nature of today social networks data streams.  ... 
doi:10.1007/978-3-319-41706-6_1 fatcat:zdoso55jzjbypkye7w3uozcjce

Overlapping Community Structure and Modular Overlaps in Complex Networks [chapter]

Qinna Wang, Eric Fleury
2013 Lecture Notes in Social Networks  
In order to find overlapping community structure of complex networks, many researchers make endeavours.  ...  Second, we propose a novel algorithm called fuzzy detection for overlapping community detection.  ...  Table 3 3 Results of fuzzy detection: ten high frequent topic keywords contained by robust clusters.  ... 
doi:10.1007/978-94-007-6359-3_2 dblp:series/lnsn/WangF13 fatcat:lpy5r74jezb5vfdoqi7qaknaeu

Finding Short Lived Events on Social Media

David Kilroy, Simon Caton, Graham Healy
2020 Irish Conference on Artificial Intelligence and Cognitive Science  
Companies have been looking to Social Media for event and trend detection for a number of years to assist in business decision making.  ...  In this paper, we show how subdividing time windows and recombining their results can significantly improve detection.  ...  In order to overcome this problem we first cluster similar events together that -along with some other processing -eliminates them being grouped together (event clustering).  ... 
dblp:conf/aics/KilroyCH20 fatcat:c7ayomygavat5dxb5lunayi4ne

Leveraging Massive User Contributions for Knowledge Extraction [chapter]

Spiros Nikolopoulos, Elisavet Chatzilari, Eirini Giannakidou, Symeon Papadopoulos, Ioannis Kompatsiaris, Athena Vakali
2011 Studies in Computational Intelligence  
The collective intelligence that emerges from the collaboration, competition, and co-ordination among individuals in social networks has opened up new opportunities for knowledge extraction.  ...  structure of tag-networks, the emerging trends and events in users tag activity, and the associations between image regions and  ...  A subdomain of topic detection research involves event recognition, that is the analysis of tags/time usage patterns along with geo-related information available in social media, to infer the event semantics  ... 
doi:10.1007/978-3-642-20344-2_16 fatcat:37r7jgrq5nceje4ir7rvm7p4ye

Event Evolution Tracking from Streaming Social Posts [article]

Pei Lee and Laks V.S. Lakshmanan and Evangelos E. Milios
2013 arXiv   pre-print
Intuitively, an event can be viewed as a dense cluster of posts with a life cycle sharing the same descriptive words. There are many previous works on event detection from social streams.  ...  Real life events, which may happen and evolve every minute, are perceived and circulated in post streams by social users.  ...  clusters, and is robust to noise.  ... 
arXiv:1311.5978v1 fatcat:stmn2xkxqbgt7fq7akw7gaze64

Islander: A Real-Time News Monitoring and Analysis System [article]

Chao-Wei Huang, Kai-Chou Yang, Zi-Yuan Chen, Hao-Chien Cheng, Po-Yu Wu, Yu-Yang Huang, Chung-Kai Hsieh, Geng-Zhi Wildsky Fann, Ting-Yin Cheng, Ethan Tu, Yun-Nung Chen
2022 arXiv   pre-print
The system allows users to browse trending topics with articles from multiple sources and perspectives.  ...  With thousands of news articles from hundreds of sources distributed and shared every day, news consumption and information acquisition have been increasingly difficult for readers.  ...  Then, we extract the union from generated results as a robust set, and add tags with high confidence from the remainings to the robust set, until the size of robust set reaches K.  ... 
arXiv:2204.11457v1 fatcat:bf26b3oue5hoblqwhwa3xi33jq

A Robust Process to Identify Pivots inside Sub-communities In Social Networks [article]

Joseph Ndong, Ibrahima Gueye
2018 arXiv   pre-print
Besides the capacity of the methodology to reduce the high dimensionality of the data, the new detection scheme is able to extract, from the sub-communities, the dense sub-groups with the definition and  ...  formulation of new quantities related to the notions of energy and co-energy.  ...  Link detection: Impact of the Co-Energy dissipation between:4-7 Events ID Number of actor participation DV Actor #4 Actor #7 (d) Co-Energy between actor 4 and actor 7 Fig. 3 .  ... 
arXiv:1804.08419v1 fatcat:3nt3ihajlnbxdabwpvxy6ysthu

Events Detection and Temporal Analysis in Social Media [chapter]

Yawei Jia, Jing Xu, Zhonghu Xu, Kai Xing
2016 Lecture Notes in Computer Science  
Individual events will form clusters in the graph of keywords for a document collection. We built a network of keywords based on their co-occurrence in documents.  ...  Clump of keywords describing an event can be used to analyse the trend of the event. The accuracy of detecting events is over eighty percents with our method.  ...  Conclusions In this paper we proposed an efficient method to extract events from social media texts streams as well as a robust algorithm to identify hot events.  ... 
doi:10.1007/978-3-319-50496-4_33 fatcat:gmm77pgbq5e7ngzbgwzy6rlhde

Social media meta-API

George Papadakis, Konstantinos Tserpes, Emmanuel Sardis, Magdalini Kardara, Athanasios Papaoikonomou, Fotis Aisopos
2012 Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion  
Finally, introduces the end user, into the new era of SNs with business applicability and better social transactions over SNs content.  ...  In this paper, we describe the external web services that SocIoS project is researching and developing, and will support with the Social Media community.  ...  Co-occurring terms belong to the same event and produce an independent cluster.  ... 
doi:10.1145/2187980.2188026 dblp:conf/www/PapadakisTSKPA12 fatcat:wz2xlvi6r5dpfloizsk2iqffoq

Robust End-User-Driven Social Media Monitoring for Law Enforcement and Emergency Monitoring [chapter]

Birgit Kirsch, Sven Giesselbach, David Knodt, Stefan Rüping
2018 Community-Oriented Policing and Technological Innovations  
Robust End-User-Driven Social Media Monitoring for Law Enforcement. . . Robust End-User-Driven Social Media Monitoring for Law Enforcement. . .  ...  Furthermore, a user can define an event-profile with a georeference and the time the event started.  ... 
doi:10.1007/978-3-319-89294-8_4 fatcat:alb5ihq2xvhqnh4w64kqgwbggm

Detecting Malicious Social Bots based on Clickstream Sequences

Peining Shi, Zhiyong Zhang, Kim-Kwang Raymond Choo
2019 IEEE Access  
INDEX TERMS Online social network, social bots, user behavior, semi-supervised clustering.  ...  A novel method of detecting malicious social bots, including both features selection based on the transition probability of clickstream sequences and semi-supervised clustering, is presented in this paper  ...  The experimental result shows that the precision of a semi-supervised clustering method based on mixed features for detecting malicious social bots with mixed malicious feature can be as high as 93.1%,  ... 
doi:10.1109/access.2019.2901864 fatcat:2sdyefxiinbhjirj7w4oyp4sj4

A History and Theory of Textual Event Detection and Recognition

Yanping Chen, Zehua Ding, Qinghua Zheng, Yongbin Qin, Ruizhang Huang, Nazaraf Shah
2020 IEEE Access  
Thresholds were used to control the depth of hierarchical events, where lower clusters are combined into one or more high layer clusters.  ...  First, social text stream data (emails in this paper) are clustered into topics with unsuper-vised methods. The email content is represented as a TF-IDF vector.  ... 
doi:10.1109/access.2020.3034907 fatcat:ng7mbplve5dttao7ro6e2623ti


Vaishali Ugale .
2015 International Journal of Research in Engineering and Technology  
We accomplish this with the application of clustering technique and later training the classifier to classify the events in PESTLE format.  ...  PESTLE based event detection approach proposed in this paper would help for PESTLE analysis of any organization.  ...  Detection of social events using robust high-order co-clustering is done in [17] . The authors in [18] make use of content extraction and aging theory as part of topic detection technique.  ... 
doi:10.15623/ijret.2015.0405112 fatcat:r6lgqlle7baxfmqdp7jsgwsmkq

Link Mining Process

Zakea Il-Agure, Hicham Noureddine Itani
2017 International Journal of Data Mining & Knowledge Management Process  
This approach is implemented through the use of a case study of realworld data (co-citation data).  ...  Many data mining and knowledge discovery methodologies and process models have been developed, with varying degrees of success, there are three main methods used to discover patterns in data; KDD, SEMMA  ...  Robustness should be robust against huge or complex social networks failures, dynamic networks, and topology changes.  ... 
doi:10.5121/ijdkp.2017.7304 fatcat:s45mefaes5btvjxyh3k6k6kfn4

Clustering Media Items Stemming from Multiple Social Networks

Thomas Steiner, Ruben Verborgh, Joaquim Gabarro, Erik Mannens, Rik Van de Walle
2013 Computer journal  
We have created and evaluated an algorithm capable of deduplicating and clustering exact-and near-duplicate media items that get published and shared on multiple social networks in the context of events  ...  When people attend events, they more and more share event-related media items publicly on social networks to let their social network contacts relive and witness the attended events.  ...  Secret Fashion Show 2012 event (face detection enabled) FIGURE 9 : 9 Top clusters ordered by cluster size for the Grammy Awards Nominations 2013 event (face detection disabled; some clusters span multiple  ... 
doi:10.1093/comjnl/bxt147 fatcat:xukygkxrejdcvgwetiexwzi54y
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