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InSocialNet: Interactive visual analytics for role—event videos

Yaohua Pan, Zhibin Niu, Jing Wu, Jiawan Zhang
2019 Computational Visual Media  
Together with social network analysis at the back end, InSocialNet supports users to investigate characters, their relationships, social roles, factions, and events in the input video.  ...  It automatically and dynamically constructs social networks from role-event videos making use of face and expression recognition, and provides a visual interface for interactive analysis of video contents  ...  We choose to use the algorithm [30] with a force directed graph to draw the co-occurrence social network.  ... 
doi:10.1007/s41095-019-0157-9 fatcat:sddnt72yivazrbub7oap5flpfe

Aspect Based Sentiments from Tweets using Co-Ranking Multi-Modal Natural Language Processing Methodologies

2020 International journal of recent technology and engineering  
To overcome the above issues, the co-ranking multi-modal natural language processing based sentiment analysis system was developed to detect the emotions from the posted tweets.  ...  From the extracted emotions, co-ranking process is applied to get the opinion effectively related to particular event.  ...  Then the twitter related emotions are derived with the help of co-ranking algorithm that is discussed in the section D. D.  ... 
doi:10.35940/ijrte.e6305.018520 fatcat:i6jrkluet5gddl5hdkoiuusaq4

Corpus-Based Syntactic-Semantic Graph Analysis

Benedikt Perak, Tajana Ban Kirigin
2020 Rasprave: Časopis Instituta za Hrvatski Jezik i Jezikoslovlje  
analyzed using a centrality algorithm that determines the overall rank of the salience and semantic relatedness to the source concept feeling. this empirical approach can be used for developing nlP methods  ...  This research exemplifies the corpus-based graph approach to the syntactic-semantic analysis of a concept feeling using the Construction Grammar Conceptual network methodology. by constructing a lexical  ...  in this communication community. the lexical network with lexemes as nodes and logDice score as relation weights enables us to analyze the graph structure by applying the graph centrality and community  ... 
doi:10.31724/rihjj.46.2.27 fatcat:nhmp4wsclfb6nfoitij3gs54xm

Opinion Relation Co-Extraction Based on Partially-Supervised Topical Relations Word Alignment Model

2020 International journal of recent technology and engineering  
Then a visual co-ranking algorithm was implemented together with the Opinion Relationship Map, to model all the candidates and to measure the confidence of each voter by defining their opinion.  ...  The efficiency of co-extracting thoughts, viewpoints and issues is enhanced effectively by using this method.  ...  Therefore, a graph of opinions is built to represent both candidates and their observed opinions along with a graphic Co-Ranking algorithm in order to evaluate increasing candidate's trust.  ... 
doi:10.35940/ijrte.e6833.038620 fatcat:ksb3qqvr25d2rbf2hvyfzoemz4

Social Tagging System for Community Detecting using NLP Technique

Mrs. C. Gomathi
2018 International Journal for Research in Applied Science and Engineering Technology  
These cross-linked social graphs model the associations between co-occurring tags, tags and community detection.  ...  In order to model network of social tag at an abstract level, we will represent such system as bipartite graphs with edges.  ...  A model of social bookmarking systems based on a set of bipartite graphs.  ... 
doi:10.22214/ijraset.2018.4279 fatcat:qldlijoa2rb2jmgty44hjh4sum

Identifying Opinion Leader in the Internet Forum

Chao Wu, Chunlin Li, Wei Yan, Youlong Luo, Xijun Mao, Shumeng Du, Mingming Li
2015 International Journal of Hybrid Information Technology  
In the experiment, the algorithm is compared with Interest-based PageRank algorithm, online time Algorithm, and Experience-based Algorithm, the result shows that the OLRA algorithm can identify opinion  ...  In this paper, we propose an algorithm called OLRA (Opinion Leader PageRank Algorithm) based on topic-field to identify opinion leaders in the Internet forum.  ...  In this paper, by using PageRank algorithm, OLRA algorithm is presented based on the user's emotional tendency and the location in the user's network Opinion-Leader-Rank algorithm.  ... 
doi:10.14257/ijhit.2015.8.11.38 fatcat:k3xvomqv4nh53eod2qdzrhrzuq

Opinion-Based Co-Occurrence Network for Identifying the Most Influential Product Features

Ashok Kumar J, Department of Information Science and Technology, Anna University, CEG Campus, Chennai, 600028, India, Abirami S, Department of Information Science and Technology, Anna University, CEG Campus, Chennai, 600028, India
2020 Maǧallaẗ al-abḥāṯ al-handasiyyaẗ  
Therefore, we present an opinion-based co-occurrence network for product reviews.  ...  We then measured the overall graph metrics and vertex metrics to characterize the network.  ...  However, the co-occurrence social network is drawn to the preprocessed data matrix using the Harel-Koren fast multiscale layout algorithm.  ... 
doi:10.36909/jer.v8i4.8369 fatcat:xd6qskiqxfh3xpupcplv5rxkwa

IEEE Access Special Section Editorial: Advanced Data Mining Methods for Social Computing

Yongqiang Zhao, Shirui Pan, Jia Wu, Huaiyu Wan, Huizhi Liang, Haishuai Wang, Huawei Shen
2020 IEEE Access  
YONGQIANG ZHAO (Member, IEEE) received the B.S. degree in automation and the M.S. and Ph.D. degrees in control theory and control engineering from Northwestern  ...  ., ''Modeling for professional athletes' social networks based on statistical machine learning,'' proposes a framework to analyze athletes' social networks.  ...  substantial relations between the named entities present in the corpus using a hierarchical graph-based clustering technique.  ... 
doi:10.1109/access.2020.3043060 fatcat:qbqk5f4ojvadlazhk2mc343sra

Behavior analysis in social networks: Challenges, technologies, and trends

Meng Wang, Ee-Peng Lim, Lei Li, Mehmet Orgun
2016 Neurocomputing  
There are however a wide range of challenges in analyzing human behavior in social networks.  ...  The fifth paper, "Discovering top-k Non-Redundant Clusterings in Attributed Graphs", introduces a novel algorithm to discover the top-k non-redundant clustering solutions in attributed graphs, i.e., a  ... 
doi:10.1016/j.neucom.2016.06.008 fatcat:x5mumxc3orduxewwvwsdxdar54

Exploring halal tourism tweets on social media

Ali Feizollah, Mohamed M. Mostafa, Ainin Sulaiman, Zalina Zakaria, Ahmad Firdaus
2021 Journal of Big Data  
To identify and analyze the topics, the study used a word list, concordance graphs, semantic network analysis, and topic-modeling approaches.  ...  A total of 33,880 tweets were used for analysis. Analysis intended to (1) identify the topics users tweet about regarding halal tourism, and (2) analyze the emotion-based sentiment of the tweets.  ...  Semantic network analysis Semantic network analysis, a branch of network and graph theory, is used to identify how words are linked to each other in a corpus [49] .  ... 
doi:10.1186/s40537-021-00463-5 fatcat:75ir27auovf3rlh4v73sipulz4

Proactive Insider Threat Detection through Graph Learning and Psychological Context

Oliver Brdiczka, Juan Liu, Bob Price, Jianqiang Shen, Akshay Patil, Richard Chow, Eugene Bart, Nicolas Ducheneaut
2012 2012 IEEE Symposium on Security and Privacy Workshops  
SA uses technologies including graph analysis, dynamic tracking, and machine learning to detect structural anomalies in large-scale information network data, while PP constructs dynamic psychological profiles  ...  SA is used to predict if and when characters quit their guild (a player association with similarities to a club or workgroup in nongaming contexts), possibly causing damage to these social groups.  ...  like to thank GLAD-PC team members Elise Weaver and Paul Sticha of HumRRO for help in understanding the psychology of adversarial insiders.  ... 
doi:10.1109/spw.2012.29 dblp:conf/sp/BrdiczkaLPSPCBD12 fatcat:4uszlerbizco5kiylzw3varm2e

Data-driven Computational Social Science: A Survey

Jun Zhang, Wei Wang, Feng Xia, Yu-Ru Lin, Hanghang Tong
2020 Big Data Research  
Specifically, the research methodologies used to address research challenges in aforementioned application domains are summarized.  ...  With the aids of the advanced research techniques, various kinds of data from diverse areas can be acquired nowadays, and they can help us look into social problems with a new eye.  ...  Various graph-based algorithms for semi-supervised learning have been proposed in the recent literature in the field of CSS.  ... 
doi:10.1016/j.bdr.2020.100145 fatcat:jazh5b3itfgmvh4pn37l4v5m7y

Context-Aware Recommender Systems for Social Networks: Review, Challenges and Opportunities

Areej Bin Suhaim, Jawad Berri
2021 IEEE Access  
Our focus is to investigate approaches and techniques used in the development of context-aware recommender systems for social networks and identify the research gaps, challenges, and opportunities in this  ...  Context-aware recommender systems dedicated to online social networks experienced noticeable growth in the last few years.  ...  The algorithm presented in [102] analyzes social networks to obtain relevant information about users and their activities, represented as a model of user's interests stored in a graph database.  ... 
doi:10.1109/access.2021.3072165 fatcat:i3igbxd44jhrzcyvynevpidcwq

Social networking data analysis tools & challenges

Androniki Sapountzi, Kostas E. Psannis
2018 Future generations computer systems  
The unfolding of every event, breaking new or trend flows in real time inside OSN triggering a surge of opinionated networked content.  ...  Key analysis practices include social network analysis, sentiment analysis, trend analysis and collaborative recommendation.  ...  Social Network Analysis Tools Graph theory is the core prominent approach in social network analysis and graph mining tools are important in investigating social structures both analytically and visually  ... 
doi:10.1016/j.future.2016.10.019 fatcat:cqlp423pv5heplujb63qo7c6yq

Centrality Measures: A Tool to Identify Key Actors in Social Networks [article]

Rishi Ranjan Singh
2020 arXiv   pre-print
Experts from several disciplines have been widely using centrality measures for analyzing large as well as complex networks.  ...  These measures rank nodes/edges in networks by quantifying a notion of the importance of nodes/edges. Ranking aids in identifying important and crucial actors in networks.  ...  Yuan [206] have used degree centrality and structural holes to analyze and forecast tourist arrivals in a tourism social network.  ... 
arXiv:2011.01627v1 fatcat:hsocyivf5jgstkled67osd6w6q
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