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Text Analytics in Social Media
[chapter]
2012
Mining Text Data
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We next discuss the research progress of applying text analytics in social media from different perspectives, and show how to improve existing approaches to text representation in social media, using real-world ...
With the large amount of data produced by various social media services, text analytics provides an effective way to meet usres' diverse information needs. ...
The authors would like to acknowledge all of the researchers in Arizona State University's Data Mining and Machine Learning Laboratory. ...
doi:10.1007/978-1-4614-3223-4_12
fatcat:ynmfabrhpjf6vils663o3rs2za
Social Networking Analysis: A State of the Art and the Effect of Semantics
2011
2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing
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The purpose is to increase awareness of the social networking analysis community about different ongoing efforts, which not only focus on the network aspect of social networks, shed some light into different ...
approaches and advance the discussion about potential future directions. ...
ACKNOWLEDGMENT This work is supported by Chevron Corp. under the joint project, Center for Interactive Smart Oilfield Technologies (CiSoft), at the University of Southern California. ...
doi:10.1109/passat/socialcom.2011.23
dblp:conf/socialcom/ChelmisP11
fatcat:jbvf6jizcjh5jbtfj2un4hqtki
Complex modeling and analysis of workplace collaboration data
2013
2013 International Conference on Collaboration Technologies and Systems (CTS)
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from human activities, at both micro (i.e. individual) and macro (i.e. community) level. ...
The vast scale (Big-data) of online human interactions impose certain challenges, such as scalable indexing and efficient retrieval of social data, which are by their nature intertwined in multiple dimensions ...
We introduce a novel social graph representation, shown in Figure 1 , which not only contains social links between users but also maintains integrated information regarding users dynamically changing ...
doi:10.1109/cts.2013.6567289
dblp:conf/cts/Chelmis13
fatcat:5qf6cfutkjfnrm7re6rvb6tzoi
Microblog-genre noise and impact on semantic annotation accuracy
2013
Proceedings of the 24th ACM Conference on Hypertext and Social Media - HT '13
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Using semantic technologies for mining and intelligent information access to microblogs is a challenging, emerging research area. ...
This paper presents a characterisation of genre-specific problems at each semantic annotation stage and the impact on subsequent stages. ...
These lead to evidence-based suggestions for future research directions towards improved semantic annotation of microblog text. ...
doi:10.1145/2481492.2481495
dblp:conf/ht/DerczynskiMAB13
fatcat:lrclf4a2zzcdth7cdvxchxnd54
Efficient Deep Learning Approach for Dimensionality Reduction using Micro blogs from Big data
2017
International Journal for Research in Applied Science and Engineering Technology
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To improve the result of dimensionality reduction, we take advantage of the semantic similarity derived from two types of micro blog specific information, namely the retweet relationship and hash tags. ...
In this project, we apply deep learning networks to map the high-dimensional representations of micro blog texts to low-dimensional representations. ...
Enriching Short Text Representation in
Liu Social media websites allow users to exchange short texts such as Tweets in microblogging, user status in friendship networks. ...
doi:10.22214/ijraset.2017.3002
fatcat:phaqfjnacvajheketlhh5h5bve
Temporal web dynamics and its application to information retrieval
2013
Proceedings of the sixth ACM international conference on Web search and data mining - WSDM '13
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. Operators for manipulating streams of interest Filter Link Visualize E. Adar, M. Dontcheva, J. Fogarty and D. Weld. Zoetrope: Interacting with the ephemeral web. ...
from query stream
Future Event Retrieval from social media
Temporal Summarization
Single Timeline
Multiple Timeline
A directional relation between two text fragments:
Text (t) and Hypothesis ...
Learning causality for news events prediction, Ontology -Linked data http://www.linkeddata.org Afghan troops were killed" Goal: For each candidate term evaluate the probability of it to appear in the future ...
doi:10.1145/2433396.2433500
dblp:conf/wsdm/RadinskyDDSDC13
fatcat:v3r5yqpnwjcezm35ux4v5eiyse
Small Survey Event Detection
[article]
2020
arXiv
pre-print
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Representation learning on graphs, rumor detection and multimodal techniques may be explored in future as well. ...
Terms are extracted from the documents, and the time series of their counts are calculated at the finest spatial and temporal scales. ...
arXiv:2011.05801v1
fatcat:xah4zzcotzfp5eadksvlqxed34
Automatic Rumor Detection on Microblogs: A Survey
[article]
2018
arXiv
pre-print
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Many efforts have been taken to defeat online rumors automatically by mining the rich content provided on the open network with machine learning techniques. ...
While the openness and convenience features of social media also foster many rumors online. Without verification, these rumors would reach thousands of users immediately and cause serious damages. ...
As for the weights of the rest two types of links: links from users to messages and links from messages to events, are not defined and set as 1 by default. ...
arXiv:1807.03505v1
fatcat:kvwukm7kofhyfd3yjlajagoxce
A semi-supervised method for topic extraction from micro postings
2015
it - Information Technology
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Typically, the human analyst needs to be actively involved during extraction and modeling to resolve ambiguities that will inevitable arise in such data and to put the model into context. ...
The applicability and utility of the proposed approach is shown for a real-world use case: the analysis of product insights and topic-driven social networks analysis for a specific product line for an ...
The Sociograph SG was created based on direct communication links implied by @-tags designating user names, including official brand accounts (see Figure 3 , left). ...
doi:10.1515/itit-2014-1078
fatcat:jzfp2bc6tbbknncehxxi2o7yjm
Sentiment Computing for the News Event Based on the Social Media Big Data
2017
IEEE Access
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More specially, based on the social media data (i.e., words and emoticons) of a news event, a word emotion association network (WEAN) is built to jointly express its semantic and emotion, which lays the ...
The explosive increasing of the social media data on the Web has created and promoted the development of the social media big data mining area welcomed by researchers from both academia and industry. ...
[13] used deep learning to learn semantic representations of user and products for document level sentiment classification. ...
doi:10.1109/access.2016.2607218
fatcat:qfojkd4r4zfrvopraehdil44ke
Personalised Information Gathering and Recommender Systems: Techniques and Trends
2013
EAI Endorsed Transactions on Scalable Information Systems
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Web information gathering aims to acquire useful and meaningful information for users from the Web. ...
However, web personalization has not yet been well-exploited; difficulties arise while selecting resources through recommender systems from a technological and social perspective. ...
However, studies show that direct application of AT model does not yield significant improvement as compared to simple term-based approach [39, 135] . ...
doi:10.4108/trans.sis.2013.01-03.e4
fatcat:o6omvzmmwvctljy24uxi6oacz4
Emoji-based Co-attention Network for Microblog Sentiment Analysis
[article]
2022
arXiv
pre-print
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2021 pre-print arXiv:2110.14227v1 fatcat:iawiip3kgrbwjd3l4ugo6hiot4
In this paper, we propose an emoji-based co-attention network that learns the mutual emotional semantics between text and emojis on microblogs. ...
increase its sensitivity to emotional semantic features. ...
This shows emoji-guided text representation learning can effectively improve the ability of the model to learn the emotional semantic. ...
arXiv:2110.14227v2
fatcat:yuuwta5p4zddldzvvycbj2cqja
Towards Deep Learning Prospects: Insights for Social Media Analytics
2019
IEEE Access
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INDEX TERMS Social media data, dynamic network, deep learning, feature learning. 36958 He has published about 70 papers in reputed international Impact Factor journals and conferences. ...
In order to the exponential development and widespread availability of digital social media (SM), analyzing these data using traditional tools and technologies is tough or even intractable. ...
d: DYNAMIC NETWORK Users linked together by friendship links, make a network of users at Facebook. ...
doi:10.1109/access.2019.2905101
fatcat:65mxyey3frdrfngvbfnfss3gpa
Semi-Supervised Variational User Identity Linkage via Noise-Aware Self-Learning
[article]
2021
arXiv
pre-print
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User identity linkage, which aims to link identities of a natural person across different social platforms, has attracted increasing research interest recently. ...
Then, a noise-aware self-learning module is designed to faithfully augment the few available annotations, which is capable of filtering noises from the pseudo-labels generated by the supervised module. ...
and microblogs to learn informative user representations for
G. Parameter Sensitivity Study social identity linkage. ...
arXiv:2112.07373v1
fatcat:e6zcnwrxifasbdmffrvqzmejiq
Semantic Enrichment of Twitter Posts for User Profile Construction on the Social Web
[chapter]
2011
Lecture Notes in Computer Science
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Given the variety and recency of topics people discuss on Twitter, semantic user profiles generated from Twitter posts moreover promise to be beneficial for other applications on the Social Web as well ...
strong impact on the construction of semantic user profiles for the Social Web. ...
In this paper we go beyond bagof-word representations and link tweets to news articles from which we extract entities to generate semantically more meaningful user profiles. ...
doi:10.1007/978-3-642-21064-8_26
fatcat:sqgr3l2od5ab7idofzqfytd3ze
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