Event Focused URL Extraction from Tweets

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Presentation transcript:

Event Focused URL Extraction from Tweets By: Chris Bridges, Carter Tat, David Chun CS 4624: Multimedia, Hypertext, and Information Access Instructor: Edward A. Fox Client: Liuqing Li April 24, 2018 Virginia Tech, Blacksburg VA 24061 Slide Owner: Chris

Outline Project Goal Overall Design Testing /Evaluation Demo References Acknowledgements

Project Goal Link existing Twitter collections and Event Focused Crawler (EFC) Classify and rank relevance of URLs in Tweets to collection using deep learning and natural language processing techniques Provide client with program that ties it all together

Overall Design

Testing/Evaluation 80% Training and 20% Testing Classifiers Decision Tree Random Decision Forest Support Vector Classifier (SVC) Gaussian NB Cross-Validated using 10 subsamples

Results Classifier Decision Tree Random Forest Support Vector (SVC) GaussianNB Test Accuracy 0.970967 0.974193 0.969354 0.790322 Cross Validation Accuracy 0.94 (+/- 0.06) 0.95 (+/- 0.06) 0.75 (+/- 0.29)

Optimal Parameters

Demo Slide Owner: David

Demo “Future Florida Gators Softball Prodigy Is the Youngest NCAA Commit of All Time”

Demo “Kentucky school shooting: 2 students killed, 18 injured”

References “Sklearn.svm.SVC.” Sklearn.svm.SVC - Scikit-Learn 0.19.1 Documentation, Web. www.scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html#sklearn.svm.SVC. Accessed 23. Apr 2018. Moreira, Gabriel. “Discovering User's Topics of Interest in Recommender Systems.” LinkedIn SlideShare, 7 July 2016, Web. www.slideshare.net/gabrielspmoreira/discovering-users-topics-of-interest-in-recommender-systems-tdc-sp-2016. Accessed 23. Apr 2018 TextMiner. “Dive Into NLTK, Part IV: Stemming and Lemmatization.” Text Mining Online, 18 July 2014, Web. www.textminingonline.com/dive-into-nltk-part-iv-stemming-and-lemmatization. Accessed 23 Apr. 2018 "Events Archive (GETAR)." Events Archive. Web. https://www.arc.vt.edu/vt-rnet/edfox/. Accessed 23 Apr. 2018. “Software Stanford Named Entity Recognizer (NER)." The Stanford Natural Language Processing Group. Web. https://nlp.stanford.edu/software/CRF-NER.shtml. Accessed 23 Apr. 2018. "Natural Language Toolkit." Natural Language Toolkit - NLTK 3.2.5 Documentation. Web. https://www.nltk.org/. Accessed 23 Apr. 2018. "Gensim: Topic Modelling for Humans." Radim Řehůřek: Machine Learning Consulting. Web. https://radimrehurek.com/gensim/ . Accessed 23 Apr. 2018.

Acknowledgements Project Client: Liuqing, Li Instructor: Edward A. Fox Global Event and Trend Archive Research (GETAR) is supported by NSF (IIS-1619028 and 1619371)

Questions?