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Improving LDA topic models for microblogs via tweet pooling and automatic labeling

Rishabh Mehrotra, Scott Sanner, Wray Buntine, Lexing Xie
2013 Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '13  
In this paper, we investigate methods to improve topics learned from Twitter content without modifying the basic machinery of LDA; we achieve this through various pooling schemes that aggregate tweets  ...  Overall, these two novel schemes lead to significantly improved LDA topic models on Twitter content.  ...  Acknowledgments NICTA is funded by the Australian Government as represented by the Department of Broadband, Communications and the Digital Economy and the Australian Research Council through the ICT Centre  ... 
doi:10.1145/2484028.2484166 dblp:conf/sigir/MehrotraSBX13 fatcat:zhdgmm76s5ezvlqugzwmvtenue

Corpus Analysis of Earthquake Related Tweets through Topic Modelling

Lany L. Maceda, Jennifer L. Llovido, Thelma D. Palaoag
2017 International Journal of Machine Learning and Computing  
Topic modeling identifies patterns in a corpus.  ...  As Twitter grows everyday, it has now become a valuable source of people's opinion. The main purpose of the study is to use Twitter, as text corpora in the attainment of disaster risk reduction.  ...  s [20] paper is to improve the quality of the Twitter Exemplar-based topic detection system.  ... 
doi:10.18178/ijmlc.2017.7.6.645 fatcat:njoo4xyotnhj7dpaxz4uxffiie

Personalized Recommendation for Online Social Networks Information: Personal Preferences and Location-Based Community Trends

Shaymaa Khater, Denis Gracanin, Hicham G. Elmongui
2017 IEEE Transactions on Computational Social Systems  
These community preferences are generally reflected in the localized trending topics.  ...  Specifically, we study how changes in the geographical community preferences can affect the individual user's interests.  ...  Our model applies trends filtering through finding the trends that are within the topics of interest in the Geo-located community.  ... 
doi:10.1109/tcss.2017.2720632 fatcat:2vwf4spdwrhwncxv22ukuzqlve

Analysis of Topic Modeling with Unpooled and Pooled Tweets and Exploration of Trends during Covid

Jaishree Ranganathan, Tsega Tsahai
2021 International Journal of Computer Science Engineering and Applications  
Topic modeling is an unsupervised algorithm to discover a hidden pattern in text documents. In this study, we explore the Latent Dirichlet Allocation (LDA) topic model algorithm.  ...  The results suggest that a pooling scheme using hashtags helps improve the topic inference results with a better coherence score.  ...  Topic Modeling using Twitter Data Social media serves as a communication tool across the world. It is used in a multitude of ways.  ... 
doi:10.5121/ijcsea.2021.11601 fatcat:skusdyt5uneifpobgsehvrurai

An Overview of Topic Discovery in Twitter Communication through Social Media Analytics

Andrey Chinnov, Pascal Kerschke, Christian Meske, Stefan Stieglitz, Heike Trautmann
2015 Americas Conference on Information Systems  
Social media provide us with a great pool of user generated content, where topic discovery may be extremely useful for businesses, politicians, researchers, and other stakeholders.  ...  However, conventional topic discovery methods, which are widely used in large text corpora, face several challenges when they are applied in social media and particularly in Twitterthe most popular microblogging  ...  For instance, the shortness problem is much more relevant for communication in Twitter than in Facebook.  ... 
dblp:conf/amcis/ChinnovKMST15 fatcat:stxgjlcvvfbg3nwrtvz53zsg54

Topic Modelling and Event Identification from Twitter Textual Data [article]

Marina Sokolova, Kanyi Huang, Stan Matwin, Joshua Ramisch, Vera Sazonova, Renee Black, Chris Orwa, Sidney Ochieng, Nanjira Sambuli
2016 arXiv   pre-print
Statistical topic modelling becomes especially important when we work with large volumes of dynamic text, e.g., Facebook or Twitter datasets.  ...  In this study, we summarize the message content of four data sets of Twitter messages relating to challenging social events in Kenya.  ...  We can assume that topic 15 identifies suspects in the attack since "shabaab", "alshabaab", "responsibility", "claim" are the highest frequency words in that topic.  ... 
arXiv:1608.02519v1 fatcat:x743ws4gcjaczkl3qyz32jmzpq

Multilingual short text categorization using convolutional neural network

Liriam Enamoto, Weigang Li
2019 The European Symposium on Artificial Neural Networks  
The experiment results show that CNN model performs better than SVM even in small dataset.  ...  One of the most meaningful use of online social media is to communicate quickly during emergency.  ...  Fig. 1 : 1 Fig. 1: CNN (1+1) model with one convolution layer and one pooling layer for text Table 1 : 1 Twitter posts classification criteria.Table 2 details each dataset used in this experiment.The  ... 
dblp:conf/esann/EnamotoL19 fatcat:uianq5uzknc65b3yxpwaccoxii

Twitter Topic Modeling by Tweet Aggregation

Asbjørn Steinskog, Jonas Therkelsen, Björn Gambäck
2017 Nordic Conference of Computational Linguistics  
Conventional topic modeling schemes, such as Latent Dirichlet Allocation, are known to perform inadequately when applied to tweets, due to the sparsity of short documents.  ...  The results show that aggregating similar tweets into individual documents significantly increases topic coherence.  ...  Author-topic model experiments Tweets from six popular Twitter users were obtained through the Twitter API, selecting users known for tweeting about different topics, so that the results would be distinguishable  ... 
dblp:conf/nodalida/SteinskogTG17 fatcat:zncpltlwt5ek5bdrwnfua3enei

"Twitter Archeology" of learning analytics and knowledge conferences

Bodong Chen, Xin Chen, Wanli Xing
2015 Proceedings of the Fifth International Conference on Learning Analytics And Knowledge - LAK '15  
Through descriptive analysis, interaction network analysis, hashtag analysis, and topic modeling, we found: extended coverage of the community over the years; increasing interactions among its members  ...  The goal of the present study was to uncover new insights about the learning analytics community by analyzing Twitter archives from the past four Learning Analytics and Knowledge (LAK) conferences.  ...  Topics Modeling of Twitter Discussion Going beyond hashtag analysis, we applied LDA to uncover underlying topics in Twitter discussion during LAK conferences.  ... 
doi:10.1145/2723576.2723584 dblp:conf/lak/ChenCX15 fatcat:25bb3ojlhrbqjo6hqnzlbb5iha

Extracting Topics with Focused Communities for Social Content Recommendation

Theodore Georgiou, Amr El Abbadi, Xifeng Yan
2017 Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW '17  
We define a way to characterize groups of users that are focused in such topics and propose an efficient and accurate algorithm to extract such communities.  ...  Through qualitative and quantitative experimentation we observe that topics with a strong community focus are interesting and more likely to catch the attention of users.  ...  And of course, content recommendation can be improved through the extraction of target groups interested in specific topics.  ... 
doi:10.1145/2998181.2998259 fatcat:b7jb6l3cjrdpbktnhfzk4e243a

Topical Alignment in Online Social Systems

Felipe Maciel Cardoso, Sandro Meloni, André Santanchè, Yamir Moreno
2019 Frontiers in Physics  
To do so, we propose an approach based on the use of hashtags to extract information topics from Twitter messages and model users' interests.  ...  In this work, we study whether users tend to be in contact with people interested in similar topics, i.e., if they are topically aligned.  ...  Our goal is to demonstrate that the information spread in Twitter is a crucial component of social dynamics through the verification of topical alignment.  ... 
doi:10.3389/fphy.2019.00058 fatcat:paljtnbevvbn3jink7qncuoh64

Topical alignment in online social systems [article]

Felipe Maciel Cardoso, Sandro Meloni, Andre Santanche, Yamir Moreno
2019 arXiv   pre-print
To do so, we propose an approach based on the use of hashtags to extract information topics from Twitter messages and model users' interests.  ...  In this work, we study whether users tend to be in contact with people interested in similar topics, i.e., if they are topically aligned.  ...  Our goal is to demonstrate that the information spread in Twitter is a crucial component of social dynamics through the verification of topical alignment.  ... 
arXiv:1707.06525v2 fatcat:ilxrxqqe4jb6ti5nrtkg2izbgq

On the use of distributed semantics of tweet metadata for user age prediction

Abhinay Pandya, Mourad Oussalah, Paola Monachesi, Panos Kostakos
2019 Future generations computer systems  
We show that our CNN-based classifier, when compared with baseline models, yields an improvement of up to 12.3% for Dutch dataset, 9.8% for English1 dataset, and 6.6% for English2 dataset in the micro-averaged  ...  This paper addresses the problem of age prediction from Twitter dataset, where the prediction issue is viewed as a classification task.  ...  The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.  ... 
doi:10.1016/j.future.2019.08.018 fatcat:glstyfyt3vbk3ggrdtwo4gvdpu

On the Use of URLs and Hashtags in Age Prediction of Twitter Users

Abhinay Pandya, Mourad Oussalah, Paola Monachesi, Panos Kostakos, Lauri Loven
2018 2018 IEEE International Conference on Information Reuse and Integration (IRI)  
We show that our CNN-based classifier, when compared with an SVM baseline model, yields an improvement of 12.3% and 6.6% in the micro-averaged F1 score on the Dutch and English datasets, respectively.  ...  This paper addresses the problem of age prediction from Twitter dataset, where the prediction issue is viewed as a classification task.  ...  Based on the hypothesis that a person's age is correlated with the topics he is interested in, we expect to see improvement in the accuracy.  ... 
doi:10.1109/iri.2018.00017 dblp:conf/iri/Pandya0MKL18 fatcat:4e5cz6wcjjerfgoscqjkzim6t4

What Does Twitter Say About Self-Regulated Learning? Mapping Tweets From 2011 to 2021

Mohammad Khalil, Gleb Belokrys
2022 Frontiers in Psychology  
This work uses three main analysis methods, descriptive, topic modeling, and geocoding analysis.  ...  In this study, we used Twitter to collect data on one of the most growing theories in education, namely Self-Regulated Learning (SRL) and carry out further analysis to investigate What Twitter says about  ...  In addition, we are extremely grateful to the two reviewers for their constructive comments which have significantly improved this work.  ... 
doi:10.3389/fpsyg.2022.820813 pmid:35282232 pmcid:PMC8907480 fatcat:dsd32rckqbb7rpvslkgrnfadbm
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