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Top keywords (global influence):
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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.
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Tip: here are the keyword queries that people search for but don't actually find in the search results.

With the launch, one after another of the sub orbital flights of Virgin Galactic, and Blue Origin, respectively, of Richard Branson, and Jeff Beezus, there has been a lot of online and offline conversations around how society should look at these initiatives, positively or negatively, they do represent a good example to evaluate the interactions and the implications of allocating private wealth of driving, common policy. And that is what we are going to talk about today. My name is David Orban, and this is the context season four episode seven

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space exploration is fascinating, and for many decades. It was the exclusive purveyor of nation states with the end of the Cold War, when the Soviet Union on one side and the United States, on the other agreed to collaborate on the next the Generation Space Station, the ISS, a space to reason started it, not right away. But for many years. A American enterpreneurs. I remember specifically talking to Burt Rutan, the inventor of the space plane. Today we call Virgin Galactic. It was complaining that the Russians were better capitalists, than the Americans because you could buy a ticket to space from them. And you couldn't buy it from NASA. For many years, and you could spend between 10 and $20 million. And then the Russians doubled the price to 240 million dollars and more. A in order to go to space, and spend about a week on the International Space Station after a years training in Baikonur, Kazakhstan. Now, this was done. Overall, by very few people. One of them, the Hungarian

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American enterpreneur, Georgia, so much he actually went twice. He, but, in total, a handful of people. However, a little more than 10 years ago, in the effort started to develop companies. Besides, the prime contractors, of the nation states space organizations, Boeing and Lockheed on the American side Roscosmos air on the energa on the Russian side. And these private companies, we're aiming to do more than launch satellites, they were aiming to bring space travel to many many more people. Hundreds 1000s possibly millions, or why not billions of people. SpaceX is on the side in this because rather than space tourism. Part of the fundamental mission of SpaceX is colonizing Mars, And whether they will succeed or not. It definitely means that they will not get distracted by bringing people in short, entertainment, rides. On the other hand, it is very much part of Virgin Galactics, and the blue origins, business model. Both are a particular type of space company that rather than bringing

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people or satellites in orbit, at least for the moment,

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achieve the trajectories that do not complete an orbit around Earth, or more. But after going up for about the 100 kilometers, they immediately go down, and then land, respectively. Virgin Galactic is a plane is on a runway and Blue Origin, with the more traditional parachutes, as far as the capsule bringing the human is concerned, and the rocket thruster, in the case of Blue Origin is capable of vertical landing. So one of the questions around it is wetter, the billionaire's funding these companies should do something else. And a lot of people complaining about the fact that this money is wasted and it should be, instead invested in eradicating hunger or poverty. In my opinion, have a complex relationship, that, That is very important to explore, but they haven't completed at least their exploration around these topics, certainly in hunger and poverty, and women's rights and 1000 other very important challenges in, in today's society around the world deserve attention. And yes, these

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deserve attention from billionaires, as much as from people who have maybe no money, but a lot of passion to give a lot of talent to dedicate to solving these, and they can be entrepreneurs, they can be investors they can be teachers and educators, policymakers, or people will have the muscle power of digging go well in, in Africa, and coordinating the effort on the ground. And now, the principle of a given group of people telling another group of people, what they should or shouldn't do, is a very old principle. And depending on the number of the first or the second group. Well, it is. In any case, a kind of a dictatorship. So, I am of the opinion that we can make certain goals, and certain efforts, popular, and by making them popular. They will attract the attention of a lot of people, they will attract resources, and hopefully they will be solved, hunger, for example, in most places in the world today is solved. Whenever there is hunger is not a question of a lack of food. It is a

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question of lack of appropriate logistics, lack of appropriate policy, or, actually, the destruction, wrote in a region by civil war, and the consequences in the destruction of crops and disruption in transporting the crops from where they grow for to where they must be eaten. Now,

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the people who complain about billionaires, Miss spending their money, have a very powerful tool. If they live in a democracy, they should elect representatives who approve legislation to tax the billionaires, and then the money appropriated by the state through taxation, can be dedicated to those challenges that these people feel are deserving, rather than based on the individual and independent decision of those billionaires. The other immediately available opportunity that each of these people have, obviously, is just rolling up their sleeves and dedicating their lives to solving those issues that are very dear to them. Now, even in those cases, by the very definition or the very description of what I just mentioned, dedicating their lives to a goal. They will make choices as well, for example, they will dedicate themselves to women's rights, which will necessarily ignore the plight of hungry, poor males. Now, I am exaggerating, obviously. But what I want to highlight is that a

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each of us decide, each of us. Listen, each of us learn, And we go on our journeys. Now, the question of whether these initiatives of space tourism are worth it is a question that is easily answered by the market. And on the surface, it would look like that these are going to be lucrative businesses both Virgin Galactic, and Blue Origin have received a lot of bookings from people who want to experience weightlessness, who want to be able to be in the as of now still very exclusive cloth, class of, astronauts, even though, earning it from a very cozy and comfy voyage of, let's say half an hour at most, rather than through a year long, grueling training in, in, in Kazakhstan, or an entire life dedicated to becoming an astronaut or a cosmonaut off the old style of the old definition. And so, we don't know for how long. A Richard Branson and Jeff Beezus will fund their hobby of space. It both can afford that for a long time for sure. And it Witter. The companies will become public, maybe,

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so that we can look at their books more in detail understanding, if they are profitable or not. For now, certainly, they are not profitable, they are losing billions and billions of dollars, it. And then the next question is, is this something that we'll have possibly regardless of this short term evaluation of the market, some positive impact on the world in general. So, the question of a technological progress, that derives from it. These kinds of endeavors, is undoubtedly a positive. If the answer is known. These kinds of research and development, bring innovation that spreads out, and the ability to launch and then land rockets is huge for many different kinds of initiatives. Imagine the possibility of rapidly delivering, not a May sale with an atomic bomb, but

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some dearly needed supplies in a remote region, in, in a matter of hours, it anywhere on the planet, that is what now we can do with the rockets that land vertically. In, imagine what we can achieve with the ability to bring in microgravity experiments that cost $100,000 Rather than millions in so many applications in so many different areas, and yes there will be a lot of people who will jump on the opportunity of taking advantage of this infrastructure that is being built, not for space tourism but for other types of initiatives. The last question is, if you care about space exploration, if these are part of what we would call, space exploration. And the answer there is today. Absolutely not. They are not part of it, they are not pushing it for what they're, I would say that the agencies of nation states have a clear advantage. If you want to design and launch a probe to an X planet or a father planet or study a comet or an asteroid, if you will definitely need the resources of the

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space agency of the United States, Russia, China, India, Japan, the European Space Agency, And well, probably not many more. Even though the number is increasing, the United Arab Emirates, launched. Deeper Space exploration missions recently as well. Space SpaceX, if successful, with its starship project, regardless of the ultimate mission of colonizing Mars with human settlements is going to definitely enter the restricted group of organizations, a private company, in this case, that is capable of deep space exploration pushing the envelope of how we understand the solar system. So, Virgin Galactic, and Blue Origin it are worthy of the conversations that they have ignited. I am personally happy that they persisted and succeeded in doing what they do. A, I think that the issue of wealth inequality is something that nation states should tackle before the fact. And now that these billionaires have their wealth, we can incentivize and we can promote certain causes for them to dedicate

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their energies to and if they choose to dedicate to the example of today. In my opinion, the balance is still positive. I am also personally passionate about space, and I congratulate both in their achievements and I'm looking forward to the next steps in this great adventure. Thank you very much for listening to this episode of the context. If you liked it, please subscribe, and enmarket as liked on the various platforms. And if you believe that it is valuable. You can become a supporter or sponsor a benefactor on slash David Orban.

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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:

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+     full table   ?     Show AI 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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AI Summarize Graph   AI Article Outline

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.

Download: TXT Report  CSV Report  More Options
Discourse Structure Advice:
Structural Gap Insight
(topics that could be better linked):
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AI: Bridge the Gap   AI: Article Outline
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 Connectors
(less visible terms that link important topics):
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AI: Select & Generate Content
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 in 4-grams
(bidirectional, for directional bigrams see the CSV table below):

⤓ 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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