01/09: Boudourides

[jmausolf]

Comment below with questions or thoughts about the reading for this week's 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.

[JuneZzj]

Thank you for presenting. I have seen pages of PDE and network graph and I am wondering besides the mathematical models and equations, is there any other way to study social network? Also, since there are many models, how do you evaluate their strengths and weakness? When you were applying those models, what did you learn the most from them? Thanks.

[luxin-tian]

Thank you in advance for your presentation. Your work introduces me to an amazing and terrific field of data science. Since I have very limited knowledge about graph theory and network science, I just wonder are there any other applications of those theory and methods in other disciplines? For example, can network science provide a new perspective for linguistic or etymological studies?

[wu-yt]

Thank you so much on presenting this exciting topic! Could you talk more about the limitation in application of graph theory and network science in social science research or in real-life problems?

[caibengbu]

This topic is really useful from personal experiences. I used to deal a lot with supply chain and global value chain research. They are using notions and methodologies coming from graph theory, discrete mathematics and other sorts of algorithm. This is very exciting and I can't wait to attend the workshop tomorrow!

[fulinguo]

Thank you very much for your presentation! I was wondering whether the models in the papers could be empirically tested using data. Also, I am interested in probabilistic methods in graph theory, which could be utilized to solve some problems when deterministic algorithms are impossible. Could you please elaborate the applications of probabilistic methods? Looking forward to your presentation tomorrow.

[tonofshell]

Thank you for sharing your work. Your methods for ego-centric decompositions in social networks were very interesting. In your examples, three groups were determined, dominating, possibly dominating, and never dominating. Could you explain more how nodes are sorted into these three groups?

[lyl010]

Thanks for giving us this presentation! Using mathematics to depict the social process and the social stable stage are really interesting! But as we can see that, mathematics simulates and deducts the final results of 'opinion propagation' and 'opinion stability', but the processes in reality may be much more diverse than what graph theory says. Processes are more often interpreted using natural language with all kinds of events, surprise, casual inference, and arts sciences seem to be better at drawing this part of picture. I am wondering if we can expect mathematics and physics to deal with this complexity of society? And are there examples that we can take away?

[Anqi-Zhou]

Thank you in advance for this amazing presentation! These materials are hard for us to totally understand, but I found it very interesting. Could you explain a little bit about the implications of Example 1 and Example 2? They seem to be two typical conditions..

[sanittawan]

Thank you for sharing your research with us. I have a tangential clarification question. In your and your co-author paper Dominating Sets and Ego-centered Decompositions in Social Network, are there any cases where the proposed algorithms won't work? You mentioned at the end of the paper that the future work is to generalize it to a directed graph. Is it possible for a social network to be modeled as a non-simple graph?

[bazirou]

Thank you for your presentation! Do you think using so complex math can really reach the results you expect? Could you explain how multi-dimensional machine learning models such as CNN combine the layers and get more precise results?

[Yiqing-Zh]

Thank you for the presentation in advance! Network analysis is an important issue in the social science field. Could you please give a few application examples in the social science of ego-centered decompositions?

[vinsonyz]

Thank you so much for your amazing presentation! I'm very interested in social network, especially in education system. So my question is how does the peer pressure come into effect in the social network to improve the performance of the students in the public school? Is there a way to define it mathematically?

[heathercchen]

Thank you in advance for your presentation! It is quite difficult for those who have no previous knowledge about this topic to fully understand this question. In the second article "Dominating Sets and Ego-Centered Decompositions in Social Networks", you take the example of Les Miserables to show an application of network analysis. What is the intuition behind that example?

[mingtao-gao]

Thank you for your presentation in advance! It appears very interesting that you use diffusion as analogue to the influence of opinions in a social network and how you build mathematical models to decompose a social network into ego-centered sub-networks. Can you provide us some examples how these models can be used in solving real life problems, for example, studying how a fake news can alter a specific social network on Facebook?

[minminfly68]

Thank you for the presentation! I would ask a more general question about mathematics model and social science? What's the relationship between mathematics model and social science? How can we use mathematics model to illustrate some traditional social science perspective, like theory? What's the biggest difference between applying mathematics model to social science and traditional approach? Thanks.

[Panyw97]

Thank you for sharing the mathematical origins of network analysis with us. It's so important to understand the mathematical theory of social networks since we need to utilize it to design our algorithms to solve and predict specific problems. In all the mathematical models, the random walk model is the most familiar one because it is used a lot in stock price prediction. Can you elaborate on the application of this model in the realm of the social networks?

[luyingjiang]

Thank you for your presentation. The discussion about utilizing graph theory to analyze the social network really gives some insights to those who are not that familiar with this topic like me. I am impressed by the math part in both papers. In the paper Dominating Sets and Ego-centered Decompositions in Social Network, for ego-centric networks with altering connections is it possible (or necessary) to track down the full networks beginning with focal nodes? If not, what alternative approach can we use? Are there any limitations to your model?

[sunying2018]

Thanks for your presentation! I am interested about the Friedkin-Johnsen Model you mentioned in the paper. Since it updated at the subsequent time by the iterative scheme, I am just curious about how fast it will converges to the equilibrium vector and what factors determine the speed of convergence.

[jsgenan]

Thank you and I am excited about your efforts in making network science a unique discipline! When it comes to ego-centric network, could you elaborate on its social science background? What are the demands from social scientists that lead you to develop this decomposition? My other question is: in this paper, we are unvealing another feature of network structure. In your opinion, what is the fundamental goal of studying the structure of a network?

[cytwill]

Thank you for the presentation! It feels good for me to see some other scholars who are also interested in opinion dynamics. I have read multiple articles about opinion dynamics, some of which also use mathematical deductions to calculate the time when the distribution of opinions in the network becomes stable. It is a good idea to take the network structure into consideration, but I think a major concern is the validation of the model, which is shared in many theoretical opinion dynamic models. I wonder if you have some suggestions to testify the effectiveness of the model with real data other than simulated data?

[nt546]

Thanks for your presentation! In your paper "Dominating sets and ego-centered decompositions in social networks", you use different structural measures to assess dominating ego-centered decompositions. I was wondering if you could provide some examples that highlight the importance of different structural measures in assessing different decompositions.

[bhargavvader]

Thank you for the talk! I'm wondering how alternate views of networks, such as those in anthropology or critical theory might be implemented in computational network science, such as Latour's Actor Network Theory.

[yalingtsui]

Thank you for your presenting. Actually I am not familiar with this field. Could you please give some explanation of the application on other social science fields?

[Yawei-Li]

Thank you for coming and presenting! After some efforts, I have to admit that the mathematical complexity is preventing me from fully understanding your work yet the question to pursue appears to be of great interest and value. This is rather disappointing because I did have some training in network theory and basic measurement of social network characteristics, yet the definitions, notations and formulas do not look familiar. Therefore, it would be great if you could provide some route maps of how I (or we) can fill this knowledge gap, what kind of methodological or theoretical knowledge should be acquired and what are the best ways to learn them.

[AllisonXiong]

Thanks for presenting your work! To be honest, the unfamiliar topic and math-heavy explanation makes it hard for me to fully keep track of your elaboration, but the idea of applying graph theory and PDEs to model the dyanamics within social network is fascinating. My question is, how do you evaluate the accuracy and/or effectiveness of your models?

[ellenhsieh]

Thank you for presenting this interesting topic! To be honest, like @AllisonXiong said, it is also hard for me to fully understand your explanation in terms of math. However, I am quite curious about how you measure people's degree of susceptibility to influence when you evaluate the social influence network. Would you mind to elaborate on the measurement of the degree of susceptibility to influence?

[SixueLiu96]

Thanks for your presentation! This paper is heavily mathematical and abstract for me. In "Dominating sets and ego-centered decompositions in social networks", the ego-centered decompositions is used here via different structural measures. I wonder is there any assumptions for this decomposition, would that be relevant to our paper? Thanks!

[jtschoi]

Thank you for your presentation. I was wondering whether this work has any connection to information transmission in a weighted and directed graph / network. For instance, Banerjee et al. (2019, REStud) consider information transmission in developing economies and consider choosing "seeds" where the said transmission can be facilitated (while not directly looking at the underlying graph structure). Do you think your study on ego-centered networks can shed light on understanding similar phenomena?