Dr. Alexander Nwala

Dr. Alexander Nwala

Asst. Professor, Data Science

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Posts by Collection

portfolio

publications

2017

  1. Alexander C. Nwala, Michele C. Weigle, Michael L. Nelson, Adam B. Ziegler, and Anastasia Aizman, “Local Memory Project: Providing Tools to Build Collections of Stories for Local Events from Local Sources,” In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL). Toronto, Ontario, Canada, June 2017, pp. 219–-228.  

2018

  1. Grant Atkins, Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “Measuring News Similarity Across Ten U.S. News Sites,” In Proceedings of the International Conference on Digital Preservation (iPres). Boston, MA, September 2018.    
  2. Shawn M. Jones, Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “The Many Shapes of Archive-It,” In Proceedings of the International Conference on Digital Preservation (iPres). Boston, MA, September 2018.    
  3. Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “Bootstrapping Web Archive Collections from Social Media,” In Proceedings of ACM Hypertext (HT). Baltimore, MD, July 2018.  
  4. Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “Scraping SERPs for archival seeds: it matters when you start,” In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL). Fort Worth, TX, June 2018, pp. 263-272.    

2019

  1. Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “Using Micro-collections in Social Media to Generate Seeds for Web Archive Collections,” In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL). Urbana-Champaign, IL, June 2019, pp. 251-–260.    

2020

  1. Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “365 Dots in 2019: Quantifying Attention of News Sources,” Poster/demo accepted at the Computation + Journalism Symposium (symposium cancelled due to COVID-19), May 2020.    
  2. Jayawardana, Yasith, Nwala, Alexander C, Jayawardena, Gavindya, Wu, Jian, Jayarathna, Sampath, Nelson, Michael L, and Giles, C Lee, “Modeling Updates of Scholarly Webpages Using Archived Data,” In Proceedings of IEEE International Conference on Big Data (IEEE BigData 2020). 2020.  

2021

  1. Alexander C. Nwala, Michele C. Weigle, and Michael L. Nelson, “Garbage, Glitter, or Gold: Assigning Multi-dimensional Quality Scores to Social Media Seeds for Web Archive Collections,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). September 2021, pp. 80-89.    
  2. Dhruv Patel, Alexander C. Nwala, Michele C. Weigle, and Michael L. Nelson, “What Did It Look Like: A service for creating website timelapses using the Memento framework,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). September 2021, pp. 340-341, poster.    

2022

  1. Christopher Torres-Lugo, Manita Pote, Alexander Nwala, and Filippo Menczer, “Manipulating Twitter Through Deletions,” In Proceedings of AAAI Conference on Web and Social Media (ICWSM). june 2022.    

2023

  1. Nwala, Alexander C., Flammini, Alessandro, and Menczer, Filippo, “A Language Framework for Modeling Social Media Account Behavior,” EPJ Data Science, Vol. 12, No. 1, 2023, p. 33.    

2024

  1. Giroux, James, Gangani, Ariyarathne, Nwala, Alexander C, and Fanelli, Cristiano, “Unmasking Social Bots: How Confident Are We?,” arXiv preprint arXiv:2407.13929, 2024.  
  2. Gangani Ariyarathne, and Alexander C. Nwala, “3DLNews: A Three-decade Dataset of US Local News Articles,” In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024). New York, NY, USA 2024. ACM, pp. 1-5.  

Conferences and Workshops (Peer-Reviewed)

  1. Christopher Torres-Lugo, Manita Pote, Alexander Nwala, and Filippo Menczer, “Manipulating Twitter Through Deletions,” In Proceedings of AAAI Conference on Web and Social Media (ICWSM). june 2022.    
  2. Alexander C. Nwala, Michele C. Weigle, and Michael L. Nelson, “Garbage, Glitter, or Gold: Assigning Multi-dimensional Quality Scores to Social Media Seeds for Web Archive Collections,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). September 2021, pp. 80-89.    
  3. Dhruv Patel, Alexander C. Nwala, Michele C. Weigle, and Michael L. Nelson, “What Did It Look Like: A service for creating website timelapses using the Memento framework,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). September 2021, pp. 340-341, poster.    
  4. Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “Using Micro-collections in Social Media to Generate Seeds for Web Archive Collections,” In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL). Urbana-Champaign, IL, June 2019, pp. 251-–260.    
  5. Grant Atkins, Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “Measuring News Similarity Across Ten U.S. News Sites,” In Proceedings of the International Conference on Digital Preservation (iPres). Boston, MA, September 2018.    
  6. Shawn M. Jones, Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “The Many Shapes of Archive-It,” In Proceedings of the International Conference on Digital Preservation (iPres). Boston, MA, September 2018.    
  7. Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “Bootstrapping Web Archive Collections from Social Media,” In Proceedings of ACM Hypertext (HT). Baltimore, MD, July 2018.  
  8. Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “Scraping SERPs for archival seeds: it matters when you start,” In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL). Fort Worth, TX, June 2018, pp. 263-272.    
  9. Alexander C. Nwala, Michele C. Weigle, Michael L. Nelson, Adam B. Ziegler, and Anastasia Aizman, “Local Memory Project: Providing Tools to Build Collections of Stories for Local Events from Local Sources,” In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL). Toronto, Ontario, Canada, June 2017, pp. 219–-228.  
  10. Jayawardana, Yasith, Nwala, Alexander C, Jayawardena, Gavindya, Wu, Jian, Jayarathna, Sampath, Nelson, Michael L, and Giles, C Lee, “Modeling Updates of Scholarly Webpages Using Archived Data,” In Proceedings of IEEE International Conference on Big Data (IEEE BigData 2020). 2020.  
  11. Alexander Nwala, and Michael L. Nelson, “A Supervised Learning Algorithm for Binary Domain Classification of Web Queries using SERPs,” In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL). 2016, pp. 237-238, Best Poster Award, 3rd place.    

Journals and Magazines

  1. Nwala, Alexander C., Flammini, Alessandro, and Menczer, Filippo, “A Language Framework for Modeling Social Media Account Behavior,” EPJ Data Science, Vol. 12, No. 1, 2023, p. 33.    
  2. Whelan, Eoin C, Nwala, Alexander C, Osgood, Christopher, and Olariu, Stephan, “Selective mutation accumulation: a computational model of the paternal age effect,” Bioinformatics, Vol. 32, No. 24, 2016, pp. 3790-3797.  
  3. He, Wu, Kshirsagar, Ashish, Nwala, Alexander, and Li, Yaohang, “Teaching Information Security with Workflow Technology–A Case Study Approach.,” Journal of Information Systems Education, Vol. 25, No. 3, 2014.  

Other (Poster Presentations, Dissertation, Misc)

  1. Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “365 Dots in 2019: Quantifying Attention of News Sources,” Poster/demo accepted at the Computation + Journalism Symposium (symposium cancelled due to COVID-19), May 2020.    

Recent Publications and Talks

  1. Nwala, Alexander C., Flammini, Alessandro, and Menczer, Filippo, “A Language Framework for Modeling Social Media Account Behavior,” EPJ Data Science, Vol. 12, No. 1, 2023, p. 33.    
  2. Christopher Torres-Lugo, Manita Pote, Alexander Nwala, and Filippo Menczer, “Manipulating Twitter Through Deletions,” In Proceedings of AAAI Conference on Web and Social Media (ICWSM). june 2022.    
  3. Alexander C. Nwala, Michele C. Weigle, and Michael L. Nelson, “Garbage, Glitter, or Gold: Assigning Multi-dimensional Quality Scores to Social Media Seeds for Web Archive Collections,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). September 2021, pp. 80-89.    
  4. Dhruv Patel, Alexander C. Nwala, Michele C. Weigle, and Michael L. Nelson, “What Did It Look Like: A service for creating website timelapses using the Memento framework,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). September 2021, pp. 340-341, poster.    
  5. Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “365 Dots in 2019: Quantifying Attention of News Sources,” Poster/demo accepted at the Computation + Journalism Symposium (symposium cancelled due to COVID-19), May 2020.    
  6. Alexander Nwala, Michele C. Weigle, and Michael L. Nelson, “Using Micro-collections in Social Media to Generate Seeds for Web Archive Collections,” In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL). Urbana-Champaign, IL, June 2019, pp. 251-–260.    
  7. Jayawardana, Yasith, Nwala, Alexander C, Jayawardena, Gavindya, Wu, Jian, Jayarathna, Sampath, Nelson, Michael L, and Giles, C Lee, “Modeling Updates of Scholarly Webpages Using Archived Data,” In Proceedings of IEEE International Conference on Big Data (IEEE BigData 2020). 2020.  

talks

teaching

CS 432/532 - Web Science

  Catalog Description: The Web has fundamentally changed how we learn, play, communicate, and work. Its influence has become so monumental that it has given birth to a new science: Web Science, or the science of decentralized information structures. Although Web Science is interdisciplinary by nature, this course will be focusing mainly on the computing aspects of the Web: how it works, how it is used, and how it can be analyzed. We will examine a number of topics including: web architecture, web characterization and analysis, web archiving, Web 2.0, social networks, collective intelligence, search engines, web mining, information diffusion on the web, and the Semantic Web. Prerequisites: Standing as an undergraduate senior, graduate student, or approval from the instructor. Read more

CS 432/532 - Web Science

  Catalog Description: The Web has fundamentally changed how we learn, play, communicate, and work. Its influence has become so monumental that it has given birth to a new science: Web Science, or the science of decentralized information structures. Although Web Science is interdisciplinary by nature, this course will be focusing mainly on the computing aspects of the Web: how it works, how it is used, and how it can be analyzed. We will examine a number of topics including: web architecture, web characterization and analysis, web archiving, Web 2.0, social networks, collective intelligence, search engines, web mining, information diffusion on the web, and the Semantic Web. Prerequisites: Standing as an undergraduate senior, graduate student, or approval from the instructor. Read more

DATA 440-03 - Web Science

  Catalog Description: The Web has fundamentally changed how we learn, play, communicate, and work. Its influence has become so monumental that it has given birth to a new science: Web Science, or the science of decentralized information structures. Although Web Science is interdisciplinary by nature, this course will be focus mainly on the computing aspects of the Web: how it works, how it is used, and how it can be analyzed. We will examine several topics including: web architecture, web characterization and analysis, web archiving, Web 2.0, social networks, (creating/detecting) social bots, collective intelligence, search engines, web mining, information diffusion on the web, Semantic Web, etc. Read more

DATA 340-02 - Network Science

  Catalog Description: Network Science – Networks are everywhere in our lives: networks of friends on social media, the Web, networks of neurons in our brains, etc. It’s amazing that such a simple representation — dots and lines — can capture a variety of relationships, whether simple or complex. In this course, we will survey a broad range of fundamental topics in network science, relevant to students from data/computer science and engineering, informatics, business, biology, physics, statistics, social sciences, etc. For example, we will explore the properties of social networks and the key role of hubs, and how directed and weighted networks affect the spread of information and misinformation in social media. These topics are important and useful in many job sectors from marketing to technology, management to design, and from biology to the arts and humanities. Read more

DATA 440-02 - Web Science

  Catalog Description: The Web has fundamentally changed how we learn, play, communicate, and work. Its influence has become so monumental that it has given birth to a new science: Web Science, or the science of decentralized information structures. Although Web Science is interdisciplinary by nature, this course will be focus mainly on the computing aspects of the Web: how it works, how it is used, and how it can be analyzed. We will examine several topics including: web architecture, web characterization and analysis, web archiving, Web 2.0, social networks, (creating/detecting) social bots, collective intelligence, search engines, web mining, information diffusion on the web, Semantic Web, etc. Read more

DATA 445-01 - Network Analysis

  Catalog Description: Networks are everywhere in our lives: networks of friends on social media, the Web, networks of neurons in our brains, etc. It’s amazing that such a simple representation — dots and lines — can capture a variety of relationships, whether simple or complex. In this course, we will survey a broad range of fundamental topics in network science, relevant to students from data/computer science and engineering, informatics, business, biology, physics, statistics, social sciences, etc. For example, we will explore the properties of social networks and the key role of hubs, and how directed and weighted networks affect the spread of information and misinformation in social media. These topics are important and useful in many job sectors from marketing to technology, management to design, and from biology to the arts and humanities. Read more

DATA 641-01 - Network Analysis

  Catalog Description: Networks are everywhere in our lives: networks of friends on social media, the Web, networks of neurons in our brains, etc. It’s amazing that such a simple representation — dots and lines — can capture a variety of relationships, whether simple or complex. In this course, we will survey a broad range of fundamental topics in network science, relevant to students from data/computer science and engineering, informatics, business, biology, physics, statistics, social sciences, etc. For example, we will explore the properties of social networks and the key role of hubs, and how directed and weighted networks affect the spread of information and misinformation in social media. These topics are important and useful in many job sectors from marketing to technology, management to design, and from biology to the arts and humanities. Read more

DATA 202-01 - Ethics in Data Science

  Catalog Description: This course provides an introduction to critical, ethical, and moral issues surrounding data and society. It blends social and technological perspectives on data with ethics, policy, and case examples. We will explore a broad range of topic — from Algorithmic Bias to Interpretability in Machine Learning — to help students develop a workable understanding of current ethical issues in data science. Moreover, the course examines the ethical questions and dilemmas that arise in the development of technologies that affect the lives of peoples. Students will debate issues surrounding bias, privacy, surveillance, discrimination, and transparency, throughout the development life cycle of applications – from dataset generation to model development and evaluation. Read more

DATA 440-07 - Web Science

  Catalog Description: The Web has fundamentally changed how we learn, play, communicate, and work. Its influence has become so monumental that it has given birth to a new science: Web Science, or the science of decentralized information structures. Although Web Science is interdisciplinary by nature, this course will be focus mainly on the computing aspects of the Web. Provides an overview of the World Wide Web and associated decentralized information structures, focusing mainly on the computing aspects of the Web: how it works, how it is used, and how it can be analyzed. Students will examine a number of topics including: web architecture, web characterization and analysis, web archiving, Web 2.0, social networks, (creating/detecting) social bots, collective intelligence, search engines, web mining, information diffusion on the web, Semantic Web, etc. Read more

DATA 691-03 - Web Science

  Catalog Description: The Web has fundamentally changed how we learn, play, communicate, and work. Its influence has become so monumental that it has given birth to a new science: Web Science, or the science of decentralized information structures. Although Web Science is interdisciplinary by nature, this course will be focus mainly on the computing aspects of the Web. Provides an overview of the World Wide Web and associated decentralized information structures, focusing mainly on the computing aspects of the Web: how it works, how it is used, and how it can be analyzed. Students will examine a number of topics including: web architecture, web characterization and analysis, web archiving, Web 2.0, social networks, (creating/detecting) social bots, collective intelligence, search engines, web mining, information diffusion on the web, Semantic Web, etc. Read more