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machine:machine learning
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Project Notes:
Top keywords (global influence):
Top topics (local contexts):
Explore the main topics and terms outlined above or see them in the excerpts from this text below.
See the relevant data in context: click here to show the excerpts from this text that contain these topics below.
Tip: use the form below to save the most relevant keywords for this search query. Or start writing your content and see how it relates to the existing search queries and results.
Tip: here are the keyword queries that people search for but don't actually find in the search results.

Welcome to this new episode of the context. I'm talking to you from Seoul, South Korea. I came here to help my daughter Giordana start her new life. Does she know what she's going to do? Well, not really. Is she going to make mistakes? Oh yeah. Plenty. And when you turn 20 as a, it was her case just a few weeks ago. That is your privilege to go out and try and see what works. And of course with the support of her friends and family and the little bit of savings that she has and Ray Skittle, it's just an exhilarating and wonderful, such an adventure. And of course she has certain plans. She just released her first K-pop song and you can look in the notes of the video to listen to it and to send it to all your friends. I hope you will like it.

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She would like to get into the world of K-pop, Korean pop music. If you heard a few years ago, the song Gangnam Style, you heard something from K-pop and then she also wants to do online social media, marketing and content creation, both video as well as content writing. If you have teams that want to add a passionate, creative and curious person including part-time that can help with these activities, you know, that she can be a very, very positive contribution to those activities. So I have had the chance of coming to Korea already over the course of the past 20 years. The country is fascinating and if you look at Asia in general, of course there are so many differences. It is amazing.

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But looking at Japan Korea and China, not China overall, but China as represented by the leading edge city of Shanghai, it is I think, interesting to look at how things evolve and how things develop both in terms of technologies that are available to build the Shinkansen in Japan or the bullet trains now in China even outperforming those or it the social technologies that are much more group and community oriented than not in Europe or, or even more so individualistic in the United States.

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When I first came here in Seoul, I was told how you always look at your glass and if it is empty, you pour to the other person who will automatically look at your glass and seeing that the design empty will pour to you. But it is bad custom to pour yourself or another quirk or accustom of the language where people referring to their family and, and sisters and brothers, they always use the plural.

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They don't say, I did this, I did that. We did my family, they always exclusively use the pool row way did this together referring to the group. The work ethic is amazing. I remember when I would be to get her with the group that hosted me in my previous trips and they would show me around the city and have lunch together and then dinner together and then karaoke key and whatever else and then come 10:00 PM 11:00 PM or midnight. They would ask me if I needed anything else or I was ready to to go to sleep. And I would say, yep, I'm ready. Absolutely. And they would very gracefully waved me goodbye. And, and that, that at the time they would go back to the office because given that they spent all the day with me, they have work to do.

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So now they are going back to the office to make sure that the work is done. This is also the kind of dedication, loyalty, and commitment that you seldom see in a, an enterprise, a corporation in the West, unless maybe you talk about a startup and the founders where this sacrifice is expected and, and, and universal, but not for, for employees in the Korean society the past 50 years where an amazing change of course before the Korean war, South Korea and North Korea being a single country where more or less on the same level of poverty. It was a developing country, but since then, South Korea exploded in its economic and social development. And it was a, a dictatorship for a few decades. It is now a democracy. And it has seen blossoming very important conglomerates Samsung for foremost, but also edgy and, and otters.

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10 plus years ago the Korean government understood that relying on these large companies and their harder production would not be enough to firmly established Korea as a leading commercial producer. It, they realized that the software layers were equally important. They were not successful breaking into computer programs, computer software. There have been some successes. Internationally. Namo web editor used to be a worldwide leading a software package that you could install on your computer in order to create web pages, editing the code, making sure in a fairly wizzywig what you see is what you get, the environment that everything would work and to get it with with, with that, there were some other successful software companies for, for personal computers. But the, the industry didn't really take off where absolutely. Korea achieved great worldwide success is in the equivalent of creating a local Hollywood both developing on what is, what are called the, the Korean drama and the

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equivalent of a soap opera or us that are not only successful locally, but I would say in a worldwide basis.

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And that is actually how my daughter Giordana learned English. She was already passionate about Korean drama at the age of 11 or 12. And the, she participated on platforms of a fan subbing communities where she would read the English subtitles of Korean drama and translate it to Italian for example. And the other area of of great success for the local content industry is what I already mentioned. Pop music K-pop is a fascinating because it is what you would call it totally artificial art form, eh, rather than having roots in folklore going back hundreds or thousands of years. However, it is an extremely rich and, and inclusive form of music. You can haveK pop in a rock, in rap, in a blues or jazz,uall kinds of styles,ucan,ubecome a K pop,usuccess stories.

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And, and the groups are also interesting, eh, how they are designed and how they are then presented. It is also an extremely competitive world where in order to succeed you really have to give everything you have. So I will definitely be following and, and, and trying to help Jordanna as much as I can from, from afar, eh, in, in seeing how she goes about what she does. She already has a YouTube channel where she learned all kinds of skills of shooting a video, editing a video in applying all kinds of special effects of course, uploading and then sharing in the appropriate manner so that it has the largest possible impact. Also with her song, she was able to find the person who would compose the music. The other person who would write the the, the, the text.

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Then she found a studio for the recording and then she ran back a, I don't know, like a dozen times to fine tune everything based on the GarageBand source that the composer provided her and this very skill of being gabled to select the, the various people needed in a, in a team and then manage them to, to collaborate and create what these then a nice packaged product. In this case, the song is itself valuable. So she has shown to be self driven and able to learn what these needed to reach her goals. That is what makes me optimistic that whatever the end result is going to be, she will be able to navigate towards the goal and Caroll the resources needed and learn the skills that are, that are necessary in her initial state.

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The most important first task was to find an apartment to rent. And here they called them rooms because actually they are all a single studio, a room like where I am right now. We're in a single space. You have the living space, the, the eh, place where you, you, you sleep the kitchen area the bathroom separated by biome, but the part of the same volume. And so yesterday we went around and the day before visiting about half a dozen different places in order to get a sense for what would it be the possible set of parameters given her a budget. And today she decided on which is the one that she wants to pick. So Shu soon she will be signing the lease agreement or the rental agreement writer and the move in and she will have her seeing Chon sole apartment address, absolutely exciting and fascinating.

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So the opportunity today of moving and experiential learning different languages and different cultures is really open to anybody. Almost regardless of of your budget. There are places that are extremely inexpensive compared to Western European or American standards. And that means that you can launch yourself if you are attracted by this opportunity, eh, at any moment because you can structure things to open up these new opportunities to yourself. For example, if you are already paying a mortgage on your home but you want to move rather than selling the house maybe in a moment in the real estate market that is not optimal, you can booted on an Airbnb while you are traveling. And there is now an entire ecosystem of providers that will help you manage the Airbnb listing. And your property, even you are, when you are not physically there, they will come and clean.

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They will make sure that everything is in order. And you will be able to pay your mortgage with the Airbnb income and maybe already partially cover your expenses as you travel. For example in Thailand, things are very cheap and wonderful. Another of my children cozy Mo just had a wonderful trip in, in Thailand and and really was able to organize things so that he would spend very, very little to, to sleep and very little to eat. So more and more people are able to experience different cultures. And I believe this is fundamental. This is very important. Contrary to what was the expectation maybe 40, 50 years ago, the interconnectedness of the world did not bring how much an ization yes, we can find the franchise chains here in soul. And if that is what we choose, we will be able to go and eat there.

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But it, the local food environment is thriving and it has not been impacted by, eh, the big multinational global franchises negatively, eh, at least as far as I can perceive it, eh, to even further if anything. And it is the franchises that have to adapt. When I was in India, I took a photo of the McDonald's menu serving vegetarian hamburgers, evidently unnecessary in a country where cows are sacred and you would not want to serve hamburgers made out of them. So these kind of re emerging of variation that even those companies that are based on standardization necessarily adapt is an interesting and an essential component of an evolutionary variation and source of the reach solutions that are found all over. Another example is how we used to condescendingly talk about the Chinese internet stifled as we thought behind the great firewall of China where all the, the platforms dev lobbed in the West couldn't penetrate because the official government policy wouldn't let them.

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But what happened is that through this protection and the progressive connection of more and more Chinese people, now hundreds of millions, I don't know what the latest numbers are. People own broadband connectivity, both a DSL or cable or fiber optic but also in ever increasing numbers through their smart phones needed and were able to eagerly adopt what the local solutions were. So rather than Google there would be Baidu and rather than Twitter or Facebook, there would be the local equivalence of a Weibo and Tencen and others to the point where quiet famously in the acceleration of these platforms leaped leapfrogged the solutions that are used today in Europe or in the U S WeChat which is kind of the Chinese equivalent of WhatsApp is much more feature rich where people not only exchange text messages, but also search and broke, restaurants pay the taxi fare and the many other functions.

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Famously QR codes have been adopted in China as the payment mechanism, eh, of choice and now are ubiquitous. And eh, the latest trend is a face recognition for many functions including payments. So the variations that can occur in culture and technology solutions are both due to the adaptation that necessarily large organizations make when they want to succeed in a local market that is open to them. This is the example of McDonald's in India putting a vegetarian burger on its menu as well as the variation comes from protected markets, developing local solutions that are eagerly adopted by those customers who necessarily have to pick from the last available to them. But these platforms potentially can also leapfrog in functionality. Those that are competing in the open environments.

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Japan, Korea and China are about just three examples of interesting, intriguing and thriving cultures in the East that are influencing through their drama, their music, their technology, their mobile phones the world. And the, I hope many of you will have the opportunity to visit, but if not to come in person at least to dig a little bit deeper in trying to understand what is going on in all of these places and to connect with people on your social networks or in other ways in order to learn about those cultures and learn about the people. Thank you very much for watching this episode of the context and the, I am looking forward to recording the next one for you in a few days. And in the meantime, I'm awaiting for your questions and your feedback and looking forward to interacting online or meeting you in person soon.

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semantic variability:
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Semantic Variability Score
— modulates diversity of the discourse network  how it works?
The score is calculated based on how modular the structure of the graph is (> 0.4 means the clusters are distinct and separate from one another = multiple perspectives). It also takes into account how the most influential nodes are dispersed among those clusters (higher % = lower concentration of power in a particular cluster).
Actionable Insight:


We distinguish 4 states of variability in your discourse. We recommend that a well-formed discourse should go through every stage during its evolution (in several iterations).

  1 - (bottom left quadrant) — biased — low variability, low diversity, one central idea (genesis and introduction stage).
  2 - (top right) - focused - medium variability and diversity, several concepts form a cluster (coherent communication stage).
  3 - (bottom right) - diversified — there are several distinct clusters of main ideas present in text, which interact on the global level but maintain specificity (optimization and reflection stage).
  4 - (left top) — dispersed — very high variability — there are disjointed bits and pieces of unrelated ideas, which can be used to construct new ideas (creative reformulation stage).

Read more in the cognitive variability help article.
Generate AI Suggestions
Your Workflow Variability:
Shows to what extent you explored all the different states of the graph, from uniform and regular to fractal and complex. Read more in the cognitive variability help article.

You can increase the score by adding content into the graph (your own and AI-generated), as well as removing the nodes from the graph to reveal latent topics and hidden patterns.
Phases to Explore:
AI Suggestions  
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Main Topical Clusters:

please, add your data to display the stats...
+     full table   ?     Show Categories

The topical clusters are comprised of the nodes (words) that tend to co-occur together in the same context (next to each other).

We use a combination of clustering and graph community detection algorithm (Blondel et al based on Louvain) to identify the groups of nodes are more densely connected together than with the rest of the network. They are aligned closer to each other on the graph using the Force Atlas algorithm (Jacomy et al) and are given a distinct color.
Most Influential Elements:
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+     Reveal Non-obvious   ?

AI Paraphrase Graph

We use the Jenks elbow cutoff algorithm to select the top prominent nodes that have significantly higher influence than the rest.

Click the Reveal Non-obvious button to remove the most influential words (or the ones you select) from the graph, to see what terms are hiding behind them.

The most influential nodes are either the ones with the highest betweenness centrality — appearing most often on the shortest path between any two randomly chosen nodes (i.e. linking the different distinct communities) — or the ones with the highest degree.
Network Structure:
The network structure indicates the level of its diversity. It is based on the modularity measure (>0.4 for medium, >0.65 for high modularity, measured with Louvain (Blondel et al 2008) community detection algorithm) in combination with the measure of influence distribution (the entropy of the top nodes' distribution among the top clusters), as well as the the percentage of nodes in the top community.

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Action Advice:
Structural Gap
(ask a research question that would link these two topics):
Reveal the Gap   ?   Generate an AI Question
A structural gap shows the two distinct communities (clusters of words) in this graph that are important, but not yet connected. That's where the new potential and innovative ideas may reside.

This measure is based on a combination of the graph's connectivity and community structure, selecting the groups of nodes that would either make the graph more connected if it's too dispersed or that would help maintain diversity if it's too connected.

Latent Topical Brokers
(less visible terms that link important topics):

These are the latent brokers between the topics: the nodes that have an unusually high rate of influence (betweenness centrality) to their freqency — meaning they may appear not as often as the most influential nodes but they are important narrative shifting points.

These are usually brokers between different clusters / communities of nodes, playing not easily noticed and yet important role in this network, like the "grey cardinals" of sorts.

Emerging Keywords

Evolution of Topics
(number of occurrences per text segment) ?
The chart shows how the main topics and the most influential keywords evolved over time. X-axis: time period (split into 10% blocks). Y-axis: cumulative number of occurrences.

Drag the slider to see how the narrative evolved over time. Select the checkbox to recalculate the metrics at every step (slower, but more precise).

Main Topics
(according to Latent Dirichlet Allocation):

LDA stands for Latent Dirichlet Allocation — it is a topic modelling algorithm based on calculating the maximum probability of the terms' co-occurrence in a particular text or a corpus.

We provide this data for you to be able to estimate the precision of the default InfraNodus topic modeling method based on text network analysis.
Most Influential Words
(main topics and words according to LDA):

We provide LDA stats for comparison purposes only. It works with English-language texts at the moment. More languages are coming soon, subscribe @noduslabs to be informed.

Sentiment Analysis

positive: | negative: | neutral:
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We analyze the sentiment of each statement to see whether it's positive, negative, or neutral. You can filter the statements by sentiment (clicking above) and see what kind of topics correlate with every mood.

The approach is based on AFINN and Emoji Sentiment Ranking

Use the Bert AI model for English, Dutch, German, French, Spanish and Italian to get more precise results (slower). Standard model is faster, works for English only, is less precise, and is based on a fixed AFINN dictionary.

Keyword Relations Analysis:

please, select the node(s) on the graph see their connections...
+   ⤓ download CSV   ?

Use this feature to compare contextual word co-occurrences for a group of selected nodes in your discourse. Expand the list by clicking the + button to see all the nodes your selected nodes are connected to. The total influence score is based on betweenness centrality measure. The higher is the number, the more important are the connections in the context of the discourse.
Top Relations / Bigrams
(both directions):

⤓ Download   ⤓ Directed Bigrams CSV   ?

The most prominent relations between the nodes that exist in this graph are shown above. We treat the graph as undirected by default. Occurrences shows the number of the times a relationship appears in a 4-gram window. Weight shows the weight of that relation.

As an option, you can also downloaded directed bigrams above, in case the direction of the relations is important (for any application other than language).

Text Statistics:
Word Count Unique Lemmas Characters Lemmas Density
Text Network Statistics:
Show Overlapping Nodes Only

⤓ Download as CSV  ⤓ Download an Excel File
Network Structure Insights
mind-viral immunity:
The higher is the network's structure diversity and the higher is the alpha in the influence propagation score, the higher is its mind-viral immunity — that is, such network will be more resilient and adaptive than a less diverse one.

In case of a discourse network, high mind-viral immunity means that the text proposes multiple points of view and propagates its influence using both highly influential concepts and smaller, secondary topics.
The higher is the diversity, the more distinct communities (topics) there are in this network, the more likely it will be pluralist.
The network structure indicates the level of its diversity. It is based on the modularity measure (>0.4 for medium, >0.65 for high modularity, measured with Louvain (Blondel et al 2008) community detection algorithm) in combination with the measure of influence distribution (the entropy of the top nodes' distribution among the top clusters), as well as the the percentage of nodes in the top community.

Influence Distribution
Topics Nodes in Top Topic Components Nodes in Top Comp
Nodes Av Degree Density Weighed Betweenness

Narrative Influence Propagation:
The chart above shows how influence propagates through the network. X-axis: lemma to lemma step (narrative chronology). Y-axis: change of influence.

The more even and rhythmical this propagation is, the stronger is the central idea or agenda (see alpha exponent below ~ 0.5 or less).

The more variability can be seen in the propagation profile, the less is the reliance on the main concepts (agenda), the stronger is the role of secondary topical clusters in the narrative.
propagation dynamics: | alpha exponent: (based on Detrended Fluctuation Analysis of influence) ?   show the chart
We plot the narrative as a time series of influence (using the words' betweenness score). We then apply detrended fluctuation analysis to identify fractality of this time series, plotting the log2 scales (x) to the log2 of accumulated fluctuations (y). If the resulting loglog relation can be approximated on a linear polyfit, there may be a power-law relation in how the influence propagates in this narrative over time (e.g. most of the time non-influential words, occasionally words with a high influence).

Using the alpha exponent of the fit (which is closely related to Hurst exponent)), we can better understand the nature of this relation: uniform (pulsating | alpha <= 0.65), variable (stationary, has long-term correlations | 0.65 < alpha <= 0.85), fractal (adaptive | 0.85 < alpha < 1.15), and complex (non-stationary | alpha >= 1.15).

For maximal diversity, adaptivity, and plurality, the narrative should be close to "fractal" (near-critical state). For fiction, essays, and some forms of poetry — "uniform". Informative texts will often have "variable + stationary" score. The "complex" state is an indicator that the text is always shifting its state.

Degree Distribution:
  calculate & show   ?
(based on kolmogorov-smirnov test) ?   switch to linear
Using this information, you can identify whether the network has scale-free / small-world (long-tail power law distribution) or random (normal, bell-shaped distribution) network properties.

This may be important for understanding the level of resilience and the dynamics of propagation in this network. E.g. scale-free networks with long degree tails are more resilient against random attacks and will propagate information across the whole structure better.
If a power-law is identified, the nodes have preferential attachment (e.g. 20% of nodes tend to get 80% of connections), and the network may be scale-free, which may indicate that it's more resilient and adaptive. Absence of power law may indicate a more equalized distribution of influence.

Kolmogorov-Smirnov test compares the distribution above to the "ideal" power-law ones (^1, ^1.5, ^2) and looks for the best fit. If the value d is below the critical value cr it is a sign that the both distributions are similar.
Please, enter a search query to visualize the difference between what people search for (related queries) and what they actually find (search results):

We will build two graphs:
1) Google search results for your query;
2) Related searches for your query (Google's SERP);
Click the Missing Content tab to see the graph that shows the difference between what people search for and what they actually find, indicating the content you could create to fulfil this gap.
Please, enter a search query to discover what else people are searching for (from Google search or AdWords suggestions):

We will build a graph of the search phrases related to your query (Google's SERP suggestions).
Find a market niche for a certain product, category, idea or service: what people are looking for but cannot yet find*

We will build two graphs:
1) the content that already exists when you make this search query (informational supply);
2) what else people are searching for when they make this query (informational demand);
You can then click the Niche tab to see the difference between the supply and the demand — what people need but do not yet find — the opportunity gap to fulfil.
Please, enter your query to visualize Google search results as a graph, so you can learn more about this topic:

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