Lu Xiao

Lu Xiao

Associate Professor

213 Hinds Hall | Phone: 315-443-1707


Welcome to my profile page! I am an associate professor at the School of Information Studies (a.k.a., iSchool) in Syracuse University. My research interests and activities are related to three broad areas: collaborative and social computing, digital humanities, and community informatics. I use a variety of research methods and approaches ranging from field observations and interviews, to UI design and prototyping, to the application and development of computational techniques for large-scale data analysis. Please feel free to stop by at my office to chat about these areas if you are interested. I am always looking for students to work together in these areas.

Before coming to Syracuse, I was an associate professor at the University of Western Ontario. I received my Ph.D. from the College of Information Sciences and Technology at Pennsylvania State University. I was a visiting professor at Syracuse from Fall 2015 to Spring 2016, and at Xerox Research Center in Europe in Summer 2015.


News (updated on April 1, 2017)

- Our paper (Taraneh Khazaei, Lu Xiao, & Robert Mercer), titled "Writing to Persuade: Analysis and Detection of Persuasive Discourse", was one of the four finalists for the Best Completed Research Paper (i.e., Lee Dirks Award for Best Paper) at 2017 iConference (Mar. 22 - 25, Wuhan, China)

- Our paper (Lu Xiao, & Niall Conroy), titled "Discourse Relations in Rationale-Containing Text-Segments", was accepted by Journal of the Association for Information Science and Technology (JASIST)

- Our poster (Daniela Fernandez Espinosa, & Lu Xiao), , titled "Twitter Users’ Privacy Concerns: What do Their Accounts’ First Names Tell Us?”, was accepted by 2017 International Conference on Social Media & Society (July 28 - 30, Toronto, Canada)

I am looking for motivated students who are interested in exploring the following research topics. Let's chat if you want to know more about what my group does on these topics:

to leverage collective intelligence in social media environments

In social media environments, users express their opinions, offer their ideas, and construct new knowledge with the others. I am interested in studying and supporting their online reasoning behavior in these processes. Currently, we explore computational approaches to identify the users' rationales or justifications (an example paper can be found here) and to predict the persuasive power of the users' messages. We also examine the design of reasoning aid tools from HCI perspective.

Leveraging collective intelligence in these digital environments implies the collection and analysis of the user generated content and the contextual data about the users' activities and behavior in the environments. This brings up an important concern - the user's privacy issue. While these data about the users or the users generated are easily accessible through the web, some users may be more privacy concerned and less comfortable of their data being used. In addition, some users may be annoyed or even scared of receiving personalized services or messages which are based on the analysis of their online data. To address this issue, we utilize user social footprints to automatically detect their privacy preferences (an example paper can be found here). Our goal is to provide support for companies to make an informed decision whether or not to exploit one’s publicly available data for personalization purposes.

to understand and facilitate the curation and analysis of human rights research data

In this research program, we first analyzed the human rights research literature to understand the reported data sources, and data analysis methods and software programs. We next surveyed human rights researchers through interviews and online questionnaires to further understand these issues (our paper about this study is available here). 

In the current stage of this research program, we have been working with an oral history research community to understand and support the curation and analysis of survivor testimonies. It is sometimes said that we live in an age of testimony. Eyewitness accounts of survivors of past mass violence are valuable in our current society. Digital environments are now central conduits for the global circulation of these stories, which allows first-person testimony to be increasingly used in human rights research and advocacy. Taking the word “curate” at its root meaning of “caring for,” as Lehrer and Milton suggest (2011), we develop innovative ways to curate survivor testimony so we can listen and analyze across, between and within individual life story recordings without losing the life story context. Our first prototype, Clock-based Keyphrase Map (CKM), uses machine learning and information visualization techniques to automatically identify common themes across different interviews and present them in a visual format. A short video about this prototype is available here

to foster informal learning in community settings

In the past, I’ve worked with local small non-profit organizations to help them develop sustainable strategies with respect to learning IT. We identified different roles a community partner would take in different stages of an IT project (an example paper can be found here). I am interested in continuing to develop this line of research. 

Two years ago, I led a multidisciplinary research group and designed a mathematics workshop model for families of children in the local communities. We implemented a series of workshops in two major cities of Canada and China respectively (a paper about the project can be here). I am interested in exploring the collaboration opportunities with public libraries and/or schools to further develop this workshop model and expand it to other STEM subjects. There has been increased interest in integrating STEM education into library services. The first Public Libraries & STEM conference in August 2015, supported by the National Science Foundation and organized by Space Science Institute’s National Center for Interactive Learning (NCIL) and the Lunar and Planetary Institute (LPI), marked the significance and potential of this line of work.


Consistent with constructivist and connectivist learning theories, my teaching method seeks to: promote intentional learning, offer authentic learning, encourage collaborative learning, nurture reflective thinking, and provide a mutual learning environment. These five principles provide a framework for my teaching guiding my curriculum design. A good educator is a reflective practitioner. To me, one of the most rewarding aspects of an academic position is the opportunity to teach and interact with students. 


Here are something interesting about me (I think :-)

- I hold a doctoral degree in Information Sciences and Technology, a Master's degree in Computer Engineering, and a Bachelor's degree in Chemical Engineering.

- I grew up in a hot and humid city in China close to the southern part. Throughout my graduate education period, I kept moving towards north starting from University of Florida. My friends were genuinely concerned that I could only graduate in North Pole. Thankfully, Penn State issued me a doctoral degree and stopped this pattern.

- I love Martial Art (I learned a little of Small Chang Quan, Small Hong Quan, Wu Style Tai Chi, Tae Kwon Do, and Chi Gong)

- I won Pop Song singing competition in middle school


Semester Course Section Title
Fall 2017 IST654 M003 Information Systems Analysis
Fall 2017 IST776 M001 Research Methods in IST
Spring 2018 IST654 M001 Information Systems Analysis
Spring 2018 IST664 M001 Natural Language Processing
Semester Course Section Title
Fall 2016 IST654 M003 Information Systems Analysis
Spring 2017 IST654 M001 Information Systems Analysis
Spring 2017 IST664 M001 Natural Language Processing