The Journal of Machine Learning Research
The author-topic model for authors and documents
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
A web-based kernel function for measuring the similarity of short text snippets
Proceedings of the 15th international conference on World Wide Web
Why we twitter: understanding microblogging usage and communities
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Proceedings of the 17th international conference on World Wide Web
Introduction to Information Retrieval
Introduction to Information Retrieval
Proceedings of the first workshop on Online social networks
Joint latent topic models for text and citations
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Topic-link LDA: joint models of topic and author community
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Connections between the lines: augmenting social networks with text
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient methods for topic model inference on streaming document collections
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Probabilistic community discovery using hierarchical latent Gaussian mixture model
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Improving similarity measures for short segments of text
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Learning author-topic models from text corpora
ACM Transactions on Information Systems (TOIS)
Labeled LDA: a supervised topic model for credit attribution in multi-labeled corpora
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
TwitterRank: finding topic-sensitive influential twitterers
Proceedings of the third ACM international conference on Web search and data mining
Joint group and topic discovery from relations and text
ICML'06 Proceedings of the 2006 conference on Statistical network analysis
Toward predicting popularity of social marketing messages
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
Comparing twitter and traditional media using topic models
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Topical keyphrase extraction from Twitter
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
A weighted multi-factor algorithm for microblog search
AMT'11 Proceedings of the 7th international conference on Active media technology
Discovering User Interest on Twitter with a Modified Author-Topic Model
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Transferring topical knowledge from auxiliary long texts for short text clustering
Proceedings of the 20th ACM international conference on Information and knowledge management
Sentiment-Preserving reduction for social media analysis
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Outage detection via real-time social stream analysis: leveraging the power of online complaints
Proceedings of the 21st international conference companion on World Wide Web
TEM: a novel perspective to modeling content onmicroblogs
Proceedings of the 21st international conference companion on World Wide Web
Representation models for text classification: a comparative analysis over three web document types
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
Modeling user posting behavior on social media
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Tagging users based on Twitter lists
International Journal of Web Engineering and Technology
Structured event retrieval over microblog archives
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Using semi-structured data for assessing research paper similarity
Information Sciences: an International Journal
Information-theoretic measures of influence based on content dynamics
Proceedings of the sixth ACM international conference on Web search and data mining
User Features and Social Networks for Topic Modeling in Online Social Media
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Whom should I follow?: identifying relevant users during crises
Proceedings of the 24th ACM Conference on Hypertext and Social Media
Emerging topic detection for organizations from microblogs
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Improving LDA topic models for microblogs via tweet pooling and automatic labeling
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
One theme in all views: modeling consensus topics in multiple contexts
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Board coherence in Pinterest: non-visual aspects of a visual site
Proceedings of the 22nd international conference on World Wide Web companion
Why people hate your app: making sense of user feedback in a mobile app store
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Whom to mention: expand the diffusion of tweets by @ recommendation on micro-blogging systems
Proceedings of the 22nd international conference on World Wide Web
A biterm topic model for short texts
Proceedings of the 22nd international conference on World Wide Web
Clustering memes in social media
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
TUCAN: Twitter user centric ANalyzer
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Dynamic multi-faceted topic discovery in twitter
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing
Crisis management knowledge from social media
Proceedings of the 18th Australasian Document Computing Symposium
Two Phase Extraction Method for Multi-label Classification of Real Life Tweets
Proceedings of International Conference on Information Integration and Web-based Applications & Services
Timeline generation: tracking individuals on twitter
Proceedings of the 23rd international conference on World wide web
Semantic Characterization of Tweets Using Topic Models: A Use Case in the Entertainment Domain
International Journal on Semantic Web & Information Systems
A statistical approach to mining customers' conversational data from social media
IBM Journal of Research and Development
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Social networks such as Facebook, LinkedIn, and Twitter have been a crucial source of information for a wide spectrum of users. In Twitter, popular information that is deemed important by the community propagates through the network. Studying the characteristics of content in the messages becomes important for a number of tasks, such as breaking news detection, personalized message recommendation, friends recommendation, sentiment analysis and others. While many researchers wish to use standard text mining tools to understand messages on Twitter, the restricted length of those messages prevents them from being employed to their full potential. We address the problem of using standard topic models in micro-blogging environments by studying how the models can be trained on the dataset. We propose several schemes to train a standard topic model and compare their quality and effectiveness through a set of carefully designed experiments from both qualitative and quantitative perspectives. We show that by training a topic model on aggregated messages we can obtain a higher quality of learned model which results in significantly better performance in two real-world classification problems. We also discuss how the state-of-the-art Author-Topic model fails to model hierarchical relationships between entities in Social Media.