Syllabus and Textbooks
The required reading will be mainly from select journal/conference articles (listed below for each lecture), which are all available online, as well as a few chapters of the following textbook:
Syllabus
Prior to every class, we provide a list of papers - select research papers relevant to a specific lecture. Students are encouraged to read these papers before the class. See further details in Policies section.
Week 1: Introduction and Overview
Ch.01 Overview
What is Twitter, a social network or a news media? Kwak, H., et al. WWW’10
Understanding the demographics of twitter users. Mislove, A., et al. AAAI’11
Week 2: Data Crawling
Week 3: Social Relations
Ch.02 Graphs
Ch.03 Strong and Weak Ties
Fragile online relationship: a first look at unfollow dynamics in twitter. Kwak, H., et al. SIGCHI’11.
The anatomy of the facebook social graph. Ugander, J., et al. arXiv’11.
Graph structure in the web. Broder, A., et al. Computer networks’00.
Week 4: Power Laws and Popularity
Ch.14 Link Analysis and Web search
Ch.18 Power Laws
Inequality and unpredictability in an artificial cultural market. Salganik, M.J., et al. Science’06.
The small world problem . Milgram S. Psychology Today’1967.
Four degrees of separation . Backstrom L., et al. WebSci’12.
Documentary: Connected: the power of six degrees. A documentary on networks, social and otherwise. 2008.
Assignment 1 (in), Assignment 2 (out).
Week 5: Information Cascades I
Ch.16 Information Cascades
Ch.19 Cascading Behavior in Networks
TED talk: How to start a movement. Sivers, D. 2010.
Assignment 2 (in), Assignment 3 (out).
Week 6: Information Cascades II
Do cascades recur? Cheng, J., et al. WWW’16.
Searching for superspreaders of information in real-world social media. Pei, S., et al. Scientific reports’14.
Emerging topic detection for organizations from microblogs. Chen, Y., et al. SIGIR’13.
Lecture: Information diffusion on Twitter. Nikolov, S. 2012.
Assignment 3 (in).
Week 7: Exam
Week 8: Spring break
Week 9: Noisy Text Processing I
Spotting spurious data with neural networks. Amiri, H. NAACL’18.
Part-of-speech tagging for twitter: annotation, features, and experiments. Gimpel, K., et al. ACL’11.
Tutorial: Crowdsourcing
Tutorial: TweetNLP
Assignment 4 (out).
Week 10: Projects
Week 11: Noisy Text Processing II
Attentive multiview text representation for differential diagnosis. Amiri, H., et al. ACL’21.
Vector of locally aggregated embeddings for text representation. Amiri, H. et al. NAACL’19.
Tutorial: Vowpal Wabbit
Assignment 4 (in), Assignment 5 (out).
Week 12: Redundancy, Specificity & Polarization in Social Media
Linguistic redundancy in twitter. Zanzotto, F.M., et al. EMNLP’11.
Global connectivity and multilinguals in the Twitter network. Hale, S.A. SIGCHI’14.
Analyzing polarization in social media. Demszky, D., et al. NAACL’19.
Predicting and analyzing language specificity in social media posts. Gao, Yifan, et al. AAAI’19.
Week 13: Search and Factuality in Social Media
Guest Lecture: Mitra Mohatarami
Overview of the trec-2014 microblog track. Lin J., et al. TREC’14.
Attentive moment retrieval in videos. Liu, M., et al. SIGIR’18.
Automatic stance detection using end-to-end memory networks. Mohtarami, M., et al. NAACL’18.
Contrastive language adaptation for cross-lingual stance detection. Mohtarami, M., et al. EMNLP’19.
Learning time to event. Dehghani, N., et al. ACL’21.
Assignment 5 (in).
Week 14: Health Informatics in Social Media
Guest Lecture: TBA
Estimating county health statistics with twitter. Culotta, A. CHI’14.
Semantic mapping of natural language input to database entries via CNNs. Korpusik, M., et al. ICASSP’17.
Toward large-scale and multi-facet analysis of first-person alcohol drinking. Amiri, H., et al. AMIA’18
Learning to estimate nutrition facts from food descriptions. Amiri, H., et al. AMIA’19
Machine learning in medicine. Rajkomar, A., et al. NEJM’19.
Week 15: Projects
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