Masters of Networks 5: A Networks of Meaning - Hackathon

Join us for “Master of Networks 5”

Why

Society is a network. Societal change arises from the fabric of interpersonal relationships. People turn to each other to share vision, build or borrow technological tools, mobilize. They seek advice, help and moral support from each other. They exchange knowledge and share resources. They meet, interact, and work together. All societal change happens in social networks.

This ceaseless exchange is collective intelligence at work. The resulting networks of associations are its signature. We can use network analysis to understand this process, and perhaps find ways to improve upon it. Are you a social scientist, a policymaker, a civil society activist reflecting on a social process? Then thinking in networks might be a great way to generate fresh, relevant questions, and seek out their answers.

Human relationships between agents involved in societal change develop through dialogue. We can access it, and take part, through means like online fora, scientific articles, news. And dialogue, in turn, with every step creates associations between concepts and ideas. As it develops, it gives rise to networks of a different type. Their nodes represent entities that surface in the dialogue, like concepts, ideas, social agents. We call these semantic networks, networks of meaning.

What

A hackathon to explore how to use semantic networks to learn about societal change in the groups that generated them.

Semantic networks tell us how the different concepts connect to each other. Are there surprises? Do apparently unrelated concepts tend to come up in the same exchanges? Does this encode some kind of tension, some change in the making?

The fascinating part is this: by looking at the network, we can extract information that no individual in the network has. The whole is greater than the sum of the parts. Collective intelligence!

But how do you encode human dialogue in a network? How do you extract meaning from it? Does the structure of a semantic network contain some kind of “big picture” for the issue discussed in the dialogue that generated it?

How

We look at semantic datasets and build them into networks. We use open-source software for network analysis. We then visualize and interrogate the network to see what we can learn. Our final aim is to prototype methodologies for extracting collective intelligent outcomes from human conversation.

We optimize for interdisciplinarity. We draw participants from at least two very different domains: network/data science and anthropology/ethnography. But any expertise, academic or not, is very welcome, from engineering to history and art. Diversity trumps ability: the advantages of interdisciplinary collaboration outweigh the extra effort to communicate across our respective languages.

Who should come

Masters of Networks 5 is open to all, and especially friendly to beginners. Scholars of any discipline, hackers, policymakers, civil society activists, and so on all have something to contribute. In the end we are all experts here. We all are part of pushing for, and against, societal change, and all humans are expert conversationalists. There’s an extra bonus for beginners: networks are easy to visualize. And when you visualize them, as we will, they are often beautiful and intuitive.

Particularly welcome are people with an interest in the future development of Internet technology. Our data are especially juicy in that domain.

Agenda

We have three synchronous sessions in three consecutive days, but otherwise offer you the option to work according to your own process either in topical smaller call rooms for your group/challenge or asynchronous.
The Hackathon will take place online on the Gather platform. The platform will stay open for all of the 3 days of the workshop and offer a central room for everyone to attend the introduction, check-in and presentation session, but also smaller topical rooms for the groups/challenges to using as it fits them.

  • 28th of April: Kickoff!

    • 10:00-11:00 CET, synchronous introduction session: to each other, to the datasets, to the tools and expertise available. > Central Room
    • Rest of the day: Hack! Work on your challenge > Challenge/Group Rooms or self-organized
  • 29th of April: Check-in

    • 10:00-12:30 CET, optional synchronous check-in session: do you want to check-in? Do you have questions? > Central Room
      • Rest of the day: Hack! Work on your challenge > Challenge/Group Rooms or self-organized
  • 30th of April: Final Presentation

    • In the morning: Hack! Work on your challenge > Challenge/Group Rooms or self-organized
    • In the afternoon: Final Presetation: Present and discuss your findings. > Central Room
    • In the evening: Connect: Optional social hanging out and networking > Central Room or Challenge/Group Rooms

Challenges:

We see at least 4 challenge but you can propose your own.

1. Visualization challenge. Create informative and beautiful visualizations starting from our data. Skills needed: domain expertise relative to the dataset(s) chosen, design, dataviz, netviz. Coordinator: @melancon

  • ​It’s not only about creativity and beauty, it’s about interactivity – a map seen as a malleable object so you can squirk information out of it.
  • It’s also about being able to specify graphical design from the tasks you’d need to conduct on the data and its representation on the screen.
  • How is a node-link view useful? How would you intuitively like to manipulate, filter or change it at will when exploring it?
  • Would you feel you need to synchronize the view with a bar chart on some statistics? A scatterplot to figure out if things correlate?

2. Interpretation challenge. How many conclusions and hypotheses can we “squeeze” from the data? Skills needed: social research, ethnography, network science. Coordinator: @amelia

  • Interpretation is at the core of the process. You play with data, you map it, and iteratively build hypothesis. In the end, you dream you would have provable claims.

3. Reduction challenge. Can we think of simple criteria to filter the data for the highest-quality content only (eg: only posts with a minimum number of comments, or of minimum length)? Does the filtering change the results? Coordinator: @alberto

4. Text mining challenge. Network analysis is cool, but you may have other methods in your toolbox: sentiment analysis, topic modelling or maybe word2vec? How about the narratives in traditional news media? Can we compare the reporting of news outlets on tech challenges to the discussions of hackers? Let’s experiment with different tools, text data and find answers to exciting social tech dilemmas!
Skills needed: Python and enthusiasm! Coordination: @kristof_gyodi, @mpalinski

X. Would you like to add your own challenge?
Every group/challenge should have a coordinator, who takes responsibility for driving it, sharing the relevant material (examples: software libraries, notes for participants, pseudo-code…). If we only have two coordinators, we’ll only have two groups. If you think you can lead a group, get in touch with us!


Data

We offer several datasets. Three of them are identical in structure, though different in that they come from different research projects and investigate different problems. Each consists of a corpus of posts from a different online conversation. Professional ethnographers have coded each corpus with annotations; each annotation associates a snippet of text in one post to one ethnographic code. Each dataset provides CSV files for posts, post authors (pseudonymized), annotations and codes, plus a documentation file compliant with the Data Package standard. The networks aspect is captured three times:

  • The posts induce a social network of interactions across the participants.
  • The codes co-occur on the same post, inducing a semantic network of associations between concepts.
  • The codes are arranged in a hierarchy.

The ethnographic datasets are:

  1. The NGI Exchange ethnographic dataset (download page). NGI Exchange is an online forum, where hundreds of people exchange views on the next-generation Internet.

  2. The POPREBEL ethnographic dataset (download page). The POPREBEL project explores the phenomenon of populism in Europe. This is a multilingual dataset.

  3. The OPENCARE ethnographic dataset (download page). The OPENCARE project explores what happens when health and social care is administered not by the state, nor by the private sector, but by communities.

    ethno dataset posts authors annotations codes
    NGI Exchange 3,935 311 5,551 1,096
    POPREBEL 2,206 313 5,679 1,448
    OPENCARE 3,676 270 5,769 1,609

The text mining datasets are:

  1. Collection of tech media articles (download page TBA). 247k tokenized articles published between 2016 and 2020.
  2. Keyword frequencies in popular tech media (download page). Dataset including i) frequency of appearances for all unigrams and bigrams in the texts; ii) average monthly change in the terms’ frequencies calculated by OLS regressions.
  3. Co-occurrences of trending keywords in popular tech media (download page). Dataset for exploring the relationship between topics.

Practical info and registration

To register for the hackathon and to receive those link please follow the link below and fill in the form:

https://tell.edgeryders.eu/15575

It will generate a post in this thread. You can also use it to introduce yourself or your own challenge.

The hackathon takes place online via the Gather Platform.
On this platform participants can literally “gather” in different virtual rooms for big and small meetings.
No downloading or installing of anything is needed ahead of time.

We will send you the link to our very own “Master of Network” gather space 1 week and also 1 h before the first session (for those who sign up late, and for those who need a reminder ;)).

(That email will include any information you might need to find the first session.)

Of course, feel also always free to comment directly in this thread and start to engage in conversation with the organisers and other participants directly here!

(As you can see in the challenge descriptions above, you can ping the coordinators of the different challenges directly here on the forum)

8 posts were merged into an existing topic: Masters of Networks 5: networks of meaning DRAFT POST

About you:


Which challenge are you most interested in?


1 Like

About you:


Which challenge are you most interested in?


About you:
I’ve spent my career developing online communities and experimenting and defining related methods. Graphs and network visualizations and analysis are a growing part of my work.

Which challenge are you most interested in?
Interpretation challenge

3 Likes

Way to go. We will be working together then :smile:

Hi Bill! Good to see you here…

I’ve spent my career developing online communities and experimenting and defining related methods.

I can vouch for this. Bill has been in the game a long time.

2 Likes

Hi John - thanks for the warm welcome. I’m really interested to dig in at the hackathon. Network science and related tools / methods have been a surprising blind spot for community builders (I’m including myself here).

2 Likes

About you:
PhD student in Economics and Complexity. Social science research interested in applying network theory, text mining, and (social) media analysis to economics-related research questions

Which challenge are you most interested in?
Text mining challenge

2 Likes

About you:
Designer, information designer

Which challenge are you most interested in?
Visualization challenge

1 Like

About you:
I’m researcher at the Centre of Research, Images, Cultures & Cognition (CRICC) at the Paris 1 Sorbonne University where I was graduate as a Ph.D in Arts and Sciences of Art. My subject is entitled “semiotic and systemic study of the material culture: the participation of the design product in the construction of culture”.

Which challenge are you most interested in?
Visualization challenge

1 Like

About you:
I am a graduate student with honors of the Master’s Degree in Digital Humanities and Digital Knowledge
(Bologna, Italy), a discipline that aims to exploit the connection between humanities and new
technologies.
My passion for literature and languages (I have a Cambridge C2 Certificate of
English Proficiency) allowed me to publish my first articles, which revolved, nevertheless, on
the enhancement of cultural objects through the lens of the digital paradigm.
Because I collaborated to the ELTeC project for my exam of Digital Text in the Humanities
(Prof. Fabio Ciotti) and proceeded to work on the computational analysis of literary texts for
both my master dissertation and the AIUCD 2021 conference
(https://aiucd2021.labcd.unipi.it/en/home-english/), the hackaton
instantly caught my attention.
During my masters, I learned to program in Python and applied this knowledge in my
dissertation and many projects (i.e. https://opensisma.github.io/ or
https://dersuchendee.github.io/variantsmining/). Having followed two classes of
Computational Linguistics and a course of Deep Learning applications, I also have some
basis of machine learning. Participating in the hackaton would mean to me to apply what I studies to face texts through empirical analysis.

Which challenge are you most interested in?
Text mining challenge

1 Like

About you:
My background is in innovation management, then I specialized in design-based approach for social and open innovation. I’ve been a design research fellow and external collaborator on design thinking projects for different Italian universities. I have been user researcher for a digital agency. I am enthused about the research phase of the design process; I’ve been practicing quali-quantitative research tools and methodologies in several context.

Which challenge are you most interested in?
Interpretation challenge

1 Like

About you:
I studied law and communications and my PhD is focusing on understanding Internet Governance through systems thinking concepts and tools. I have very basic coding experience (but not enough to do anything independently except for exercises) and I’m just about to embark on a big dataset analysis in which I have started interpreting it and visualising parts of it.

Which challenge are you most interested in?
Interpretation challenge

1 Like

About you:
I’m a doctoral researcher at the Vrije Universiteit Brussels in the Communication Science department. I have a political science background in cybersecurity (mostly the policy field) and have done some small-scale ethnographic study a few years ago about Antivaxxers on Facebook and Reddit.

Which challenge are you most interested in?
Interpretation challenge

1 Like

About you:
Computational social scientist (Ph.D with expertise in social network analysis, R, Python and some text mining.

Which challenge are you most interested in?
Text mining challenge

1 Like

About you:
I am working on the Poprebel project as an auxiliary coder. In my own work that is mostly based on qualitative, in-depth interviews or discourse analysis of media texts, I have worked with Atlas.ti mostly. I have never used Atlas’ query tools with logic syntaxes, similar to the ones in SPSS. Regarding SPSS, I am only a basic user. To sum up: I do not have any refined skills in programming, informatics, mathematical logic, network visualisations etc.

#team_ethno-poprebel (group/challenge)

Which challenge are you most interested in?
Visualization challenge

1 Like