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Your Project Notes
Interpret graph data, save ideas, AI content, and analytics reports. Auto-Generate from Analytics
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.

Top 10 AI Tools in 2023 That Will Make Your Life Easier https://techncruncher.blogspot.com/2023/01/top-10-ai-tools-in-2023-that-will-make.html

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Top 10 AI Content Generator & Writer Tools in 2022 https://techncruncher.blogspot.com/2022/11/top-10-ai-content-generator-writer.html

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Beginner Guide to CJ Affiliate (Commission Junction) in 2022 https://techncruncher.blogspot.com/2022/09/cj-affiliate-ultimate-guide-to.html

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TOP 11 AI MARKETING TOOLS YOU SHOULD USE (Updated 2022) https://techncruncher.blogspot.com/2022/07/top-10-ai-marketing-tools-you-should-use.html

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Most Frequently Asked Questions About Affiliate Marketing https://techncruncher.blogspot.com/2022/06/most-frequently-asked-questions-about.html

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What is Blockchain: Everything You Need to Know (2022) https://techncruncher.blogspot.com/2022/04/what-is-blockchain-everything-you-need.html

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ProWritingAid VS Grammarly: Which Grammar Checker is Better in (2022) ? https://techncruncher.blogspot.com/2022/03/prowritingaid-vs-grammarly-which.html

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Sellfy Review 2022: How Good Is This Ecommerce Platform? https://techncruncher.blogspot.com/2022/03/sellfy-review-2022-how-good-is-this.html

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Ahrefs vs SEMrush: Which SEO Tool Should You Use? https://techncruncher.blogspot.com/2022/03/ahrefs-vs-semrush-which-seo-tool-should.html

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Top 10 Best PLR(Private Label Rights) Websites | Which One You Should Join in 2022? https://techncruncher.blogspot.com/2022/02/top-10-best-plrprivate-label-rights.html

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Canva Review 2022: Details, Pricing & Features https://techncruncher.blogspot.com/2022/02/canva-review-2022-details-pricing.html

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Top 7 Best Wordpress Plugin Of All Time https://techncruncher.blogspot.com/2022/02/top-7-best-wordpress-plugin-of-all-time.html

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Ginger VS Grammarly: Which Grammar Checker is Better in (2022) ? https://techncruncher.blogspot.com/2022/02/ginger-vs-grammarly-which-grammar.html

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Most Frequently Asked Questions About NFTs(Non-Fungible Tokens) https://techncruncher.blogspot.com/2022/02/most-frequently-asked-questions-about.html

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10 Best Chrome Extensions That Are Perfect for Everyone https://techncruncher.blogspot.com/2022/01/10-best-chrome-extensions-that-are.html

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Most Frequently Asked Questions About Email Marketing https://techncruncher.blogspot.com/2022/01/most-frequently-asked-questions-about.html

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7 Free Websites Every Content Creator Needs to Know https://techncruncher.blogspot.com/2022/01/7-free-websites-every-content-creator.html

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Top 9 Free AI Tools That Make Your Life Easier https://techncruncher.blogspot.com/2022/01/top-9-free-ai-tools-that-make-your-life.html

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The Download: how we can limit global warming, and GPT-4’s early adopters https://www.technologyreview.com/2023/03/21/1070106/download-how-we-can-limit-global-warming-gpt-4s-early-adopters/

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How AI experts are using GPT-4 https://www.technologyreview.com/2023/03/21/1070102/how-ai-experts-are-using-gpt-4/

   edit   deselect   + to AI

 

Language models might be able to self-correct biases—if you ask them https://www.technologyreview.com/2023/03/20/1070067/language-models-may-be-able-to-self-correct-biases-if-you-ask-them-to/

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The UN just handed out an urgent climate to-do list. Here’s what it says. https://www.technologyreview.com/2023/03/20/1070070/urgent-climate-to-do-list-ipcc/

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The Download: weight loss drugs, and a new abortion fight frontier https://www.technologyreview.com/2023/03/20/1070064/download-weight-loss-drugs-new-abortion-fight-frontier/

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Texas is trying out new tactics to restrict access to abortion pills online https://www.technologyreview.com/2023/03/20/1070042/texas-new-tactics-to-restrict-access-to-abortion-pills-online-isp/

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Weight-loss injections have taken over the internet. But what does this mean for people IRL? https://www.technologyreview.com/2023/03/20/1070037/weight-loss-injections-societal-impact-ozempic/

   edit   deselect   + to AI

 

A new paradigm for managing data https://www.technologyreview.com/2023/03/17/1069688/a-new-paradigm-for-managing-data/

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The Download: China’s version of ChatGPT, and protecting our brain data https://www.technologyreview.com/2023/03/17/1070008/download-china-version-chatgpt-protecting-brain-data/

   edit   deselect   + to AI

 

Tech that aims to read your mind and probe your memories is already here https://www.technologyreview.com/2023/03/17/1069897/tech-read-your-mind-probe-your-memories/

   edit   deselect   + to AI

 

Virtuix targets Omni One VR treadmills at home consumers https://venturebeat.com/games/virtuix-targets-omni-one-vr-treadmills-at-home-consumers/

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Defining endpoint security in a zero-trust world https://venturebeat.com/security/defining-endpoint-security-in-a-zero-trust-world/

   edit   deselect   + to AI

 

Twitch lays off over 400 staff amid Amazon downsizing https://venturebeat.com/games/twitch-lay-offs-400-staff-amazon-downsizing/

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Anything but small: Micro events bring big benefits https://venturebeat.com/virtual/anything-but-small-micro-events-bring-big-benefits/

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Immutable and Polygon Labs create a strategic alliance for Web3 gaming https://venturebeat.com/games/immutable-and-polygon-labs-create-a-strategic-alliance-for-web3-gaming/

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Augmented intelligence for everyone everywhere https://venturebeat.com/enterprise-analytics/augmented-intelligence-for-everyone-everywhere/

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PC and console sales are down, but the market is stabilizing | Newzoo https://venturebeat.com/games/pc-and-console-sales-are-down-but-the-market-is-stabilizing-newzoo/

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This week in data: What matters (and what doesn’t) in the data world https://venturebeat.com/data-infrastructure/this-week-in-data-what-matters-and-what-doesnt-in-the-data-world/

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Riot and Prime Gaming renew deal for in-game rewards, esports https://venturebeat.com/games/riot-games-prime-gaming-partnership-renewed-in-game-content-esports/

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Life by You is a life simulator from Paradox Interactive https://venturebeat.com/games/life-by-you-is-a-life-simulator-from-paradox-interactive/

   edit   deselect   + to AI

 

Roblox launches generative AI materials & coding tools https://venturebeat.com/games/roblox-launches-generative-ai-materials-coding-tools-gdc-2023/

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Subway Surfers reaches 4B lifetime downloads thanks to TikTok https://venturebeat.com/games/subway-surfers-reaches-4b-lifetime-downloads/

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With GPT-4, dangers of ‘Stochastic Parrots’ remain, say researchers. No wonder OpenAI CEO is a ‘bit scared’ | The AI Beat https://venturebeat.com/ai/with-gpt-4-dangers-of-stochastic-parrots-remain-say-researchers-no-wonder-openai-ceo-is-a-bit-scared-the-ai-beat/

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Netflix announces next games, including a Mighty Quest title https://venturebeat.com/games/netflix-announces-next-games-including-a-mighty-quest-title/

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Respawn opens new location in Madison to support Apex Legends https://venturebeat.com/games/respawn-opens-new-location-in-madison-to-support-apex-legends/

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Spatial launches beta creator tools for gamified web experiences https://venturebeat.com/games/spatial-launches-beta-creator-tools-for-gamified-web-experiences/

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Tech investor Weili Dai unveils Story Machine generative AI game creation platform https://venturebeat.com/metaverse/tech-investor-weili-dai-unveils-story-machines-generative-ai-game-creation-platform/

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Scuti and NBALab let gamers earn rewards and digital collectibles https://venturebeat.com/games/scuti-and-nbalab-let-gamers-earn-rewards-and-digital-collectibles/

   edit   deselect   + to AI

 

Flying Sheep Studios gets $1.2M in German government funding for metaverse game https://venturebeat.com/games/flying-sheep-studios-gets-german-government-funding-for-metaverse-game/

   edit   deselect   + to AI

 

Dream Games opens London office after Royal Match success https://venturebeat.com/games/dream-games-opens-london-office-after-royal-match-success/

   edit   deselect   + to AI

 

How to make sense of trending commerce innovations https://venturebeat.com/virtual/how-to-make-sense-of-trending-commerce-innovations/

   edit   deselect   + to AI

 

5 ways ChatGPT could shape enterprise search in 2023 https://venturebeat.com/enterprise-analytics/5-ways-chatgpt-could-shape-enterprise-search-in-2023/

   edit   deselect   + to AI

 

No storage, no cry: Sinking the data storage barrier https://venturebeat.com/data-infrastructure/no-storage-no-cry-sinking-the-data-storage-barrier/

   edit   deselect   + to AI

 

How AI is driving the future of technology https://venturebeat.com/ai/how-ai-is-driving-the-future-of-technology/

   edit   deselect   + to AI

 

Twitter’s fraud problem isn’t too hard to solve https://venturebeat.com/security/twitters-fraud-problem-isnt-too-hard-to-solve/

   edit   deselect   + to AI

 

Amazon is laying off another 9,000 workers https://arstechnica.com/?p=1925311

   edit   deselect   + to AI

 

Anthropic introduces Claude, a “more steerable” AI competitor to ChatGPT https://arstechnica.com/?p=1924161

   edit   deselect   + to AI

 

Google tells users of some Android phones: Nuke voice calling to avoid infection https://arstechnica.com/?p=1925040

   edit   deselect   + to AI

 

AI-imager Midjourney v5 stuns with photorealistic images—and 5-fingered hands https://arstechnica.com/?p=1924539

   edit   deselect   + to AI

 

Federal agency hacked by 2 groups thanks to flaw that went unpatched for 4 years https://arstechnica.com/?p=1924743

   edit   deselect   + to AI

 

Free data-center heat is allegedly saving a struggling public pool $24K a year https://arstechnica.com/?p=1924624

   edit   deselect   + to AI

 

Microsoft 365’s AI-powered Copilot is like an omniscient version of Clippy https://arstechnica.com/?p=1924573

   edit   deselect   + to AI

 

Baidu shares fall after Ernie AI chatbot demo disappoints https://arstechnica.com/?p=1924504

   edit   deselect   + to AI

 

OpenAI checked to see whether GPT-4 could take over the world https://arstechnica.com/?p=1924246

   edit   deselect   + to AI

 

Security firm Rubrik is latest to be felled by GoAnywhere vulnerability https://arstechnica.com/?p=1924411

   edit   deselect   + to AI

 

Hilariously sad: My great mobile provider, Mint, will sell to T-Mobile for $1.35B https://arstechnica.com/?p=1924196

   edit   deselect   + to AI

 

Still using authenticators for MFA? Software for sale can hack you anyway https://arstechnica.com/?p=1924036

   edit   deselect   + to AI

 

Microsoft Teams is adding 3D avatars for people who want to turn their webcams off https://arstechnica.com/?p=1923940

   edit   deselect   + to AI

 

Amazon unveils three satellite user terminals, plans broadband service in 2024 https://arstechnica.com/?p=1923953

   edit   deselect   + to AI

 

OpenAI’s GPT-4 exhibits “human-level performance” on professional benchmarks https://arstechnica.com/?p=1923938

   edit   deselect   + to AI

 

Ransomware attacks have entered a heinous new phase https://arstechnica.com/?p=1923896

   edit   deselect   + to AI

 

You can now run a GPT-3-level AI model on your laptop, phone, and Raspberry Pi https://arstechnica.com/?p=1923645

   edit   deselect   + to AI

 

Botnet that knows your name and quotes your email is back with new tricks https://arstechnica.com/?p=1923714

   edit   deselect   + to AI

 

GM plans to let you talk to your car with ChatGPT, Knight Rider-style https://arstechnica.com/?p=1923478

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Get ready to meet the Chat GPT clones https://arstechnica.com/?p=1923204

   edit   deselect   + to AI

 

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semantic variability:
×  ⁝⁝ 
×  ⁝⁝ 
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:

N/A

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  
×  ⁝⁝ 
Main Topical Clusters & High-Level Ideas
  ?
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.
please, add your data to display the stats...
+     full table     AI: Reveal High-Level Ideas

AI: Summarize Topics   AI: Explore Selected

Most Influential Keywords & Concepts
  ?
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.

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

Click the Reveal Underlying Ideas button to remove the most influential words (or the ones you select) from the graph, to see what terms are hiding behind them.
please, add your data to display the stats...
+      ↻    Reveal Underlying Ideas

AI: Summarize Key Statements   AI: Topical Outline
Network Structure:
N/A
?
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
Structural Gap Insight
(topics to connect)   ?
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.
N/A
Highlight in Network   ↻ Show Another Gap  
AI: Insight Question   AI: Bridge the Gap  
 
Discourse Entrance Points
(concepts with the highest influence / frequency ratio)   ?
These nodes have unusually high rate of influence (betweenness centrality) to their frequency — meaning they may appear not as often as the most influential nodes but they are important narrative shifting points.

These are usually effective entrance points into the discourse, as they link different topics together and have high inlfuence, but not too many connections, which makes them more accessible.
N/A
↻ Undo Selection AI: Select & Generate Content

Emerging Keywords
N/A

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):
loading...
 ?  

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):
loading...

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:
reset filter    ?  

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.

Concept Relation Analysis:

please, select the node(s) on the graph or in the table below to 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
0
0
0
0
Text Network Statistics:
Show Overlapping Nodes Only

⤓ Download as CSV  ⤓ Download an Excel File
Discourse Network Structure Insights
 
mind-viral immunity:
N/A
  ?
stucture:
N/A
  ?
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.

We recommend to try to increase mind-viral immunity for texts that have a low score and to decrease it for texts that have a high score. This ensures that your discourse will be open, but not dispersed.
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.

We recommend to aim for Diversified structure if you're in the Biased or Focused score range and to aim for the Focused structure if you're in the Dispersed score range.

Modularity
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Influence Distribution
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%
Topics Nodes in Top Topic Components Nodes in Top Comp
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0
%
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0
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Nodes Av Degree Density Weighed Betweenness
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0
0
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Discourse Advice:
N/A
AI: Develop the Discourse
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.
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