10/01: Fall Welcome Mixer

[shevajia]

Comment below with one speaker (and/or a paper by the speaker) whom you wish to see at our workshop.

Please make your comments by Wednesday 11:59 PM, and upvote at least five of your peers' comments on Thursday prior to the workshop. You need to use 'thumbs-up' for your reactions to count towards 'top comments,' but you can use other emojis on top of the thumbs up.

[shevajia]

I would like to see Geoffrey West, a fascinating speaker with fascinating work.

[jamesallenevans]

Hanna Wallach, Senior Research Scientist and Computational Social Scientist at Microsoft Research. Hanna has developed a number of powerful techniques for social analysis from the perspective of deep learning, tensor factorization and a number of other tools that have enabled the analysis of the unique forms of social data for novel insight. She served as the program and then general chair of the NeurIPS and so is aware of a wide range of emerging computational opportunities. And she's an awesome speaker.

[rkcatipon]

Kate Starbird would be an amazing speaker! Dr. Starbird is a leading disinformation and misinformation researcher from the University of Washington Human Centered Design & Engineering school where she directs the Emerging Capacities of Mass Participation (emCOMP) lab. Her current work touches on the Covid infodemic, the crisis of misinformation we're currently experiencing.

[william-wei-zhu]

Berk Can Deniz, PhD student at the Organizational Behavior program of Stanford Business School. Here is a fascinating paper that applies novel computational methods on a historical archive of US newspaper websites to show that "the adoption of A/B testing ...undermines the pursuit of novelty while encourages the search for incremental improvements." Here is his personal website.

[wanxii]

Sendhil Mullainathan: Professor Mullainathan is leading the Center for Applied Artificial Intelligence at Chicago Booth. Their work at the center covers diverse fields, including finance, healthcare, public policy, education, and behavioral science with the applications of AI.

[wanxii]

David C. Parkes: Professor Parkes from Harvard University works on algorithmic economics. One of his current papers focused on designing an "AI economist" to examine tax policies.

[robertorg]

I think Margaret Roberts from UC San Diego would be a great speaker. She uses methods of automated content analysis to study censorship and propaganda in China. Her research addresses questions like what kind of content is more likely to be censored online or what news content is driven by the state or by the market.

[Yaweili19]

I'd like to see Margaret Roberts. Apart from what @robertorg said, she is also an excellent speaker. Her presentations are interesting and easy to follow.

[a-bosko]

Brooke Foucault Welles is a Professor at Northeastern University. She studies the link between social networks and human behavior, which is relevant to the topics we are currently studying. She also co-authored a book called The Oxford Handbook of Networked Communication, which discusses the effect that networked communication has on how individuals act in the real world. Her research is very interesting and relevant to computation.

[luckycindyyx]

Prof. Yun Zhou is a social demographer and family sociologist at the University of Michigan. With a theory-driven mixed-methods approach, her research examines social inequality and state-market-family relations through the lens of gender, marriage, and reproduction.

Her work combines statistical analysis of survey data, original in-depth interviews, and agent-based computational modeling, showing a great combination of qualitative and computational social science analysis.

https://yunzhousociology.com/

[k-partha]

Prof. Michal Kosinski, a big data and AI researcher at Stanford, is a fantastic choice. His work has explored the scary amount of predictive power contained within Facebook data (using SVD, ML) - his methods were closely related to that used by Cambridge Analytica (he was one of the first to ring alarm bells on their unethical use of data).

His work is quintessential CSS and I would highly suggest looking him up (He's a star). https://www.michalkosinski.com/

[jinfei1125]

I would say Prof. Susan Athey! Her research interests are in Artificial Intelligence and Economics, econometrics and machine learning, such as using machine learning to predict the performance of economic policy. I read her papers before and really admire her. This is a YouTube video, you can find more! https://www.youtube.com/watch?v=BNLx_AHjYuU&ab_channel=CEGAVideos Her homepage: https://athey.people.stanford.edu/research

[romanticmonkey]

Professor Nicole Ellison from the School of Information at the University of Michigan, she has extensive experience in online communications. I'm very interested in her current research about "bad behavior" in virtual reality settings. Her website: http://www-personal.umich.edu/~enicole/

[Raychanan]

As long as you're interested in social media or text analysis, you'll probably like Yinxian Zhang.

I highly recommend the paper Nationalism on Weibo: Towards a Multifaceted Understanding of Chinese Nationalism by Yinxian Zhang, which was selected as the best paper of the year by the top journal The China Quarterly. Yinxian Zhang uses content analysis to discuss nationalist sentiments in China, using textual data from Weibo (Chinese Twitter). Their findings were surprising in that they found that nationalists are not xenophobes who stand on a united front, but rather have different likes and dislikes towards the so-called enemies of China; at the same time, nationalists are not unconditionally supportive of the government, but are likely to incorporate liberal views to question the government's authority.

Yinxian Zhang is a China Public Policy Postdoctoral Fellow at the Ash Center at Harvard. Yinxian’s research focuses on public opinion, ideology, the (online) public sphere, and state-society relations in China. Her work combines qualitative and computational methods to explore the nature of, and the changes in, the Chinese public sphere under the influence of state control. Yinxian received her M.A. and Ph.D. in sociology from the University of Chicago.

Here is her paper and CV.

[bowen-w-zheng]

Prof. Elias Bareinboim from Department of Computer Science in Columbia. Prof. Bareinboim focuses on how to make robust causal or counterfactual claims with big data. Here's a short paper on PNAS that surveys current methods of causal inference in the context of big data. His work is particularly relevant to CSS, as computational social scientists often care about causal inference and also work with big data that are observational or combined from different data sources. His homepage: https://causalai.net/

[Qiuyu-Li]

I know some faculty members in our university have done excellent jobs with data. For example, Professor Christopher Blattman and Oeindrila Dube tried to use machine learning to predict conflict spots in Indonesia and Colombia, and Professor Amir Jina coordinated with environmental scientists to estimate the economic impact of climate change. But they seem to be employing the novel tools only recently. Maybe recommendations from previous students are better fits to provide us with a comprehensive picture of this area. By the way, I would name Yuval Noah Harari, the author of Sapiens: A Brief History of Humankind (2014) and Homo Deus: A Brief History of Tomorrow (2016), if I have to!

[nwrim]

Prof. Tom Griffiths from the Department of Psychology and Computer Science at Princeton University. He and graduate students working in his lab recently participated in a very interesting workshop in CogSci 2020 on Scaling Cognitive Science. I enjoyed the talk very much and will love to see him talk in our workshop! He visited us two years ago, so maybe a little too soon to invite him back, but I wasn't here two years ago... I highly recommend his book Algorithms to live by and his paper Rethinking experiment design as algorithm design on CrowdML – NIPS '16 if anybody is interested!

[heathercchen]

I would like to see Dr. Aad Ruiter, who is a professor at University of Amsterdam, to come to our workshop virtually. He has published a paper, Approximating Walrasian Equilibria in Computational Economics. The paper is quite novel since most computational economics papers are employing these methods to deal with macro problems and theories. What he does provides us is a new way of utilizing compuational methods to proving traditional micro economic theories.

[siruizhou]

Jessica Hullman, Associate Professor of Computer Science and Medill School of Journalism at Northwestern University. Dr. Hullman develops tools and theoretical frameworks about people thinking effectively about data, combining approaches from visualization, cognitive science and AI. Her work aims to help more people make sense of complex information, and in particular to reason about data under uncertainty. Interpreting and communicating data with less ambiguity is important for computational social scientists. We can learn from her about effective visualization not only as a research tool but also as a research topic.

[linghui-wu]

It would be a good opportunity if we could invite Professor Jonathan Dingle from Booth to deliver a speech on his researches that combines economics and computational techniques.

[bakerwho]

I'd love for our very own Alex Campolo at the Stevanovich Institute for the Formation of Knowledge to give us a talk. He's been writing on the history of data visualization and tackles some fascinating questions about the history of 'statistics' and 'data' as sources of knowledge. He also explores epistemological questions about modern AI and the 'knowledge' embodied in decision making algorithms.

[yutianlai]

It would be great if we have Jennifer Pan, a political scientist from the communication department of Stanford. I always find her research methods fascinating and she might give important insights on how we should approach our research questions.

[boyafu]

I will be excited to see Dr. Joscha Legewie, the John L. Loeb Associate Professor of the Social Sciences at Harvard University, at our workshop. His work examines the social processes leading to inequality, and utilizes "big data as a promising source for future social science research". See his homepage for more information.

[wanitchayap]

I would love to have Prof. Ettinger, an assistant professor in UChicago Department of Linguistics, at our workshop. Her works focus on an intersection among NLP, linguistics, and cognitive science, which I think is very interesting. She is also a fantastic teacher and speaker.

[mintaow]

I just received a post from the Center for Data and Computing (CDAC) at the University of Chicago through email, and I discovered some really exciting research projects from faculties at CDAC. They all have a great computational component, but still have a tight connection with the real-world problems.

So I would like to have the opportunity to have Jamin Saxon at our workshop. He was previously a postdoctoral fellow with the Harris School of Public Policy and the Center for Spatial Data Science of the University of Chicago.

[harryx113]

I'd also like to have Prof. Ettinger for the same reasons mentioned by Mint

[tianyueniu]

I would be very excited to see Dr Richard Thaler or Dr John List for topics in behavioral/experimental economics at our workshop.

[lulululugagaga]

I hope to have professors from Stanford University to share their experiences in computational journalism in the chaos of new media age. It would be very exciting!

http://cjlab.stanford.edu/exploring-computational-journalism/

[ydeng117]

I hope to have Professor Kate Crawford to share her researches on social implications for the AI industry.

[zixu12]

I would like to see Sandra González-Bailón, an associate professor at the Annenberg School for Communication in the University of Pennsylvania. She also leads the research group DiMeNet: Digital Media, Networks, and Political Communication. I am interested in her latest book Decoding the Social World to know why sometimes individual acts such as tweets lead to unexpected consequences. Here is the link of the trailer of the book.

[JadeBenson]

I think Dr. Guy "Bud" Tribble, Vice President of Software Technology at Apple, would be a fascinating speaker. Recently, he has been involved with the ground-breaking collaboration between Apple and Google to develop a contract tracing approach for the covid-19 pandemic (https://www.cnbc.com/2020/04/28/apple-iphone-contact-tracing-how-it-came-together.html). He is also a fierce privacy advocate and testified to Congress about the importance of federal privacy legislation (https://www.judiciary.senate.gov/imo/media/doc/11-5-10%20Tribble%20Testimony.pdf). Dr. Tribble could speak about how CSS is being utilized by private companies to address the current pandemic, and he would have an interesting ethical critique of how to use these methods responsibly.

[kthomas14]

I think that Dr. Julian Jara-Ettinger would be a great speaker. He is an Assistant Professor of Psychology at Yale University. He uses computational models to study behavior and to test cognitive theories with a focus on early childhood.

[LFShan]

I think Nate Read Silver would be an amazing speaker. He is a graduate of the University of Chicago and the founder of the FiveThirtyEight website (https://fivethirtyeight.com). He uses data to analyze and provide quantitative aspects of political and sports issues.

[chun-hu]

I'd also love to have Sendhil Mullainathan from Booth to discuss the application of AI in different industries.

[cytwill]

I would like to recommend Jason Weston and Oksana Yakhnenko, the Google scholars who developed the TransE algorithms for embedding-based analysis of multi-relational data. This technique is super useful in the analysis of knowledge graphs, which is a type of more complex networks where the edges have different meanings (relations) to connect different types of nodes. This provides the potentials to combine pure social networks with behavior data to study different communities from a more integral perspective. Besides, a serial of related methods like TransR, TransD have also been proposed afterward, I would hope to hear some comparisons between these methods and the data or network structure requirements and problems they are best fitted into.

Here is the TransE model link

[JuneZzj]

I would like to recommend Shan Huang from University of Washington, Foster School. She major interest is on data analysis and social network and I have read the paper she published "Social Advertising Effectiveness Across Products: A Large-Scale Field Experiment". Thanks!

[chrismaurice0]

I would recommend inviting Ibram X. Kendi. He, and his book "How to Be an Antiracist", received a plethora of attention this summer after the death of George Floyd, Ahmaud Arbery, and Beronna Taylor and subsequent protests. As social scientists, I believe we should all strive to incorporate anti-racism into our lives, lesson plans, and research. Kendi argues being "not racist" is not enough; instead, we must actively and consistently stand against racism, or, as he puts it, be antiracist. In his books and speeches, Kendi provides the tools and strategies for how to be a part of an antiracist community. By inviting him to our workshops, we would be afforded the opportunity to discuss how to incorporate antiracism into our community of computational social scientists.

[xxicheng]

I would be very appreciative if we have Dr. Nicholas Christakis, who is a sociologist and physician who conducts research in the areas of social networks and biosocial science at Yale University. He focuses on two topics: (1) the social, mathematical, and biological rules governing how social networks form (“connection”), and (2) the social and biological implications of how they operate to influence thoughts, feelings, and behaviors (“contagion”). You can find more on his website.

[RuoyunTan]

I would very much like to invite David Jurgens from the School of Information, the University of Michigan, to talk to us about his research in computational social science.

[alevi98]

I would like to invite Dr. Alex Pentland from the Human Dynamics Lab at MIT. Dr. Pentland has written best-selling books such as Social Physics and he also contributed to the Lazer et al article that we had to read for class! His book was part of what inspired me to apply for this program.

[qishenfu1]

I would recommend Dr. Wang Miao, Assistant Professor at the Department of Business Statistics & Econometrics, Guanghua School of Management, Peking University. I am deeply impressed by his paper "Identifying Causal Effects With Proxy Variables of an Unmeasured Confounder", which introduces a new method to solve the unmeasured confounding problem in observational studies. I think this method is very useful in empirical social sciences, which help us do more effective and efficient data analysis.

[jkatz913]

Professor Zeev Maoz from UC Davis. Professor Maoz applies network analysis to answer questions pertaining to international relations. Some of the specific topics that his papers have addressed include alliance networks and predictive models of interstate conflict.

[Dxu1]

I would be excited to see Prof. Susan Athey from Stanford Graduate School of Business to talk about her work and the implication of artificial intelligence on economics. I find her work on online media competition very interesting

[MegicLF]

I would like to recommend Dr. Tianshu Sun from USC Marshall School of Business to give a talk on his forthcoming paper, Displaying Things in Common to Encourage Friendship Formation: A Large Randomized Field Experiment. This paper is really attractive as it discusses the impact of online social network on friendship formation via a large field experiment implemented by an IT-facilitated intervention.

[egemenpamukcu]

I'd also love to see Nicholas Christakis of Yale University to give a talk about his work on social networks and behavioral genetics/social neuroscience. I was particularly moved by his book Blueprint: The Evolutionary Origins of a Good Society He investigates what kind of social groups (in terms of composition and interaction patterns) manage to flourish and answers the how and why of fundamental social abilities of Homo sapiens such as showing affection, engaging in cooperation, and communicating learned information.

Since Professor Christakis's name was already mentioned above, my other suggestion would be Ola Rosling. He is the son of the legendary public health expert Hans Rosling and he is one of the founders and the president of the Gapminder foundation which is a non-profit promoting sustainable development via brilliant usage of statistics and data visualization. The foundation also developed the Trendalyzer software which was later acquired by Google and Ola Rosling also served as the Product Manager of Google Public Data for a while. I cannot recommend the book Factfulness enough, which is the product of his collaboration with his wife Anna Rosling and his late father.

[jsoll1]

I'd be excited to see Professor Dan Ariely give a talk!

[mikepackard415]

David Krakauer, President of Santa Fe Institute, would be a great speaker. His work "focuses on the evolutionary history of information processing mechanisms in biology and culture." One paper of his that is particularly interesting/inspiring to me is titled The Information Theory of Individuality.

[bjcliang-uchi]

I propose Professor Scott Page from the University of Michigan. He has written five books: “The Model Thinker – What you need to know to make data work for you” – stresses the application of ensembles of models to make sense of complex phenomena; “The Diversity [Bonus] – How Great Teams Pay Off in the Knowledge Economy” the follow-up and expansion on the themes in The Difference; “The Difference”, which demonstrates the benefits and costs of diversity in social contexts, Complex Adaptive Social Systems (with John Miller), which provides an introduction to complexity theory, and, most recently, Diversity and Complexity, which explores the contributions of diversity within complex systems.

[shenyc16]

I would like to recommend Judea Pearl from Computer Science Department, UCLA. He is known as one of the greatest pioneers of Bayesian Networks and won Turing Award in 2011 for his outstanding contributions in the field of artificial intelligence. I learned about him through his latest popular science book, The Book of Why: The New Science of Cause and Effect, in which he thoroughly elaborates on the meaning and significance of causal revolution, bringing inspirations for new breakthroughs in AI.

[Yutong0828]

Dr.Michal W.Kosinski, the associate Professor of Organizational Behavior at Stanford, would be a great speaker. His research interests mainly focus on individual differences in behavior, preferences, and performance and linking personality with a broad range of organizational and social outcomes in business practice. Specifically, he uses various computational methods in his research, including machine learning, data mining, and observational studies involving millions of participants. He was a psychology major throughout schooling years, but is now a professor in business school. With intensive application of computational methods in research and real-life cases, I am sure that he could give us much insights from both academic and industrial perspectives.