05/05: David Lazer

[shevajia]

Comment below with a well-developed question or comment about the reading for this week's workshop. These are individual questions and comments.

Please post your question by Wednesday 11:59 PM, and upvote at least three 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.

[y8script]

Dear Prof. Lazer, thank you for sharing your research on social network data analysis with us! My question is about quasi-experiment or natural experiments based on social network data. So far I've only seen the implementation of natural experiments on a very limited set of topics and manipulations. Do you think it is possible to expand the application of natural experiments with advanced causal modeling?

[FrederickZhengHe]

Hi Professor Lazer, thanks very much for your presentation. I noticed that for the voter file data, you picked up Twitter users whose locations are within the US. But people could fake their location on Twitter, so will it seriously affect the credibility of the data used in your research? Thanks!

[qishenfu1]

Hi Prof. Lazer, I like your research topic a lot! Really looking forward to tomorrow's presentation. I am curious about the international generalizability of your research, i.e., whether your findings can be generalized to other countries in the world? If yes, to what extent? Thank you!

[XTang685]

Hi Professor Lazer, thank you so much for your work. Social network data analysis is a really interesting topic. Could you please talk more about how your research can be used in our daily life?

[boyafu]

Hi Professor Lazer, thank you so much for sharing your work! I find the mixed study of social media and survey data really interesting. On the other hand, anonymity may cause disparities in people's online and offline behavior. I wonder what (further) research design could capture the feature. Thanks!

[Hai1218]

Thank you for coming to our Computational Social Science Workshop, Professor Lazer!

I think the research chooses an interesting and convenient way to operationalized fake news, as it is hard to systematical define what is real and what not. But there is the problem of bias arises from narrative disparity. If editorial rigors were the qualifying factor for news realness, then many of the political narrative nowadays that is right leaning would be disproportionally categorized as fake - as right wing medias generally is hold editorially un-esteemed(which is valid in many levels). Essentially, I am trying to point out is that the operationalization of fake news is "tainted" with political bias and narrative.

I was also curious why, when you present the different political affiliation groups's probability density estimates of feed with shared fake news, you separated out 'superconsumers' and 'supersharers' out of extreme right. Is that a conscious, intentional analytical move? If so then, do you assume the super-groups are more right leaning than extreme right, then?

[AllisonXiong]

Hi Professor Lazer, thanks for sharing your work! I've been interested in research on misinformation on soail media platform and have read several works by your lab. My question is, in the study of Twitter accounts, the data is inevitably muddled by bots and trolls. What do you find to be the best practice to detect and deal with such accounts?

[Toushirow1]

Hi Professor Lazer, thanks for your sharing! I hope to know if there is an experiment that tests the effect of fake news on public opinion, and the motivations for sharing this fake news. How can computational methods help us to conduct this research? Furthermore, will the widely spread of fake news weaken the credibility of those true news? Thanks!

[nswxin]

Dear Professor Lazer, This is a late comment, so I won't ask any questions but share some personal ideas on the issue raised in the paper. First, I really admire your research and classification of fake news. I do think they are hazarding the democratic progress of a country. In addition, your finding is really meaningful and can serve as solid evidence for the necessity of platform intervention in information transportation. Perhaps if a platform cannot do the job well, the government should implement laws and regulations on the similar issues.