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total nodes:  extend
 
InfraNodus
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.

Climate emergency: world 'may have crossed tipping points’ https://www.theguardian.com/environment/2019/nov/27/climate-emergency-world-may-have-crossed-tipping-points

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Clive James, writer, broadcaster and TV critic, dies aged 80 https://www.theguardian.com/culture/2019/nov/27/clive-james-writer-broadcaster-and-tv-critic-dies-aged-80

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Jeremy Corbyn reveals dossier 'proving NHS up for sale' https://www.theguardian.com/society/2019/nov/27/jeremy-corbyn-reveals-dossier-proving-nhs-up-for-sale

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Trump was briefed on whistleblower before releasing Ukraine aid – officials https://www.theguardian.com/us-news/2019/nov/27/trump-whistleblower-complaint-ukraine-aid

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Bronze cockerel to be returned to Nigeria by Cambridge college https://www.theguardian.com/education/2019/nov/27/bronze-cockerel-to-be-returned-to-nigeria-by-cambridge-college

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Daphne Caruana Galizia: police arrest Maltese PM's ex-chief of staff https://www.theguardian.com/world/2019/nov/27/daphne-caruana-galizia-police-quiz-malta-pms-ex-chief-of-staff

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Sir Jonathan Miller, writer and director, dies aged 85 https://www.theguardian.com/stage/2019/nov/27/jonathan-miller-writer-and-director-dies-aged-85

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Facebook's only Dutch factchecker quits over political ad exemption https://www.theguardian.com/technology/2019/nov/27/facebook-only-dutch-factchecker-quits-over-political-ad-exemption

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Cocaine seized from 'narco-submarine' in Spain was likely headed for UK https://www.theguardian.com/world/2019/nov/27/police-in-spain-find-three-tonnes-of-cocaine-in-narco-submarine

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Bad luck may have caused Neanderthals' extinction – study https://www.theguardian.com/science/2019/nov/27/bad-luck-may-have-caused-neanderthals-extinction-study

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Hungary pulls out of Eurovision amid rise in anti-LGBTQ+ rhetoric https://www.theguardian.com/tv-and-radio/2019/nov/27/hungary-pulls-out-of-eurovision-amid-rise-in-anti-lgbt-rhetoric

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The last divided capital in the world: 'Do they want us to believe we should be separated?' - video https://www.theguardian.com/cities/video/2019/nov/27/the-last-divided-capital-in-the-world-do-they-want-us-to-believe-we-should-be-separated-video

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'We can stop our children being poisoned': the fight for a lead-free Cleveland https://www.theguardian.com/cities/2019/nov/27/we-can-stop-our-children-being-poisoned-the-fight-for-a-lead-free-cleveland

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Real Madrid: film festival puts city's forgotten district on map https://www.theguardian.com/cities/2019/nov/22/real-madrid-film-festival-puts-citys-forgotten-district-on-map

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Alexandria is an invisible city: we live in it, but cannot see it https://www.theguardian.com/cities/2019/nov/22/alexandria-is-an-invisible-city-we-live-in-it-but-cannot-see-it

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‘Evo Morales Is Like a Father to Us’ https://www.nytimes.com/2019/11/27/world/americas/evo-morales-bolivia-coca.html?emc=rss&partner=rss

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Where the Nurse Prescribes Heroin https://www.nytimes.com/2019/11/27/world/europe/heroin-scotland-drug-use.html?emc=rss&partner=rss

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Japan’s Support for Gay Marriage Is Soaring. But Can It Become Law? https://www.nytimes.com/2019/11/27/world/asia/japan-gay-marriage.html?emc=rss&partner=rss

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Godfrey Gao, ‘Mortal Instruments’ Actor, Dies While Filming TV Show https://www.nytimes.com/2019/11/27/world/asia/Godfrey-Gao-dies-reality-television.html?emc=rss&partner=rss

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In Scotland, Brexit Is on the Line. So Is the Future of the U.K. https://www.nytimes.com/2019/11/27/world/europe/uk-general-election-scotland.html?emc=rss&partner=rss

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Sri Lankan Critics Fear a Crackdown Is Underway, and Some Flee https://www.nytimes.com/2019/11/27/world/asia/sri-lanka-rajapaksa-crackdown.html?emc=rss&partner=rss

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Albania Starts to Grasp Earthquake Toll https://www.nytimes.com/2019/11/27/world/europe/albania-earthquake.html?emc=rss&partner=rss

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Bangladesh Sentences 7 to Death Over 2016 Bakery Attack https://www.nytimes.com/2019/11/27/world/asia/bangladesh-bakery-attack.html?emc=rss&partner=rss

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Dresden Museum Partly Reopens After Jewelry Heist https://www.nytimes.com/2019/11/27/world/europe/dresden-green-room-museum.html?emc=rss&partner=rss

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Death of Colombian Teenager Drives Protesters Back to Streets https://www.nytimes.com/2019/11/26/world/americas/colombia-protests.html?emc=rss&partner=rss

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Trump Says U.S. Will Designate Drug Cartels in Mexico as Terrorist Groups https://www.nytimes.com/2019/11/26/us/trump-drug-cartels-terrorists.html?emc=rss&partner=rss

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Beijing Was Confident Its Hong Kong Allies Would Win. After the Election, It Went Silent. https://www.nytimes.com/2019/11/26/world/asia/china-hong-kong-protests-election.html?emc=rss&partner=rss

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U.S. Envoy Says Afghans Coerced Retraction of Rape Allegations https://www.nytimes.com/2019/11/26/world/asia/afghanistan-rapes-coerced-confession.html?emc=rss&partner=rss

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Giuliani Pursued Business in Ukraine While Pushing for Inquiries for Trump https://www.nytimes.com/2019/11/27/nyregion/giuliani-ukraine-business-trump.html?emc=rss&partner=rss

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Texas, Thanksgiving, Duke: Your Wednesday Briefing https://www.nytimes.com/2019/11/27/briefing/texas-thanksgiving-duke.html?emc=rss&partner=rss

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Corbyn claims dossier shows NHS at risk from US trade deal https://www.ft.com/content/5b403814-1111-11ea-a7e6-62bf4f9e548a

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How the commercial drone market became big business https://www.ft.com/content/cbd0d81a-0d40-11ea-bb52-34c8d9dc6d84

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Man City stake sale breaks valuation record for a sports group https://www.ft.com/content/1c082178-104b-11ea-a7e6-62bf4f9e548a

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Von der Leyen’s Brussels team gains MEP approval https://www.ft.com/content/e87da276-110b-11ea-a7e6-62bf4f9e548a

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Iceland and New Look set to change hands again https://www.ft.com/content/b4e48100-10fc-11ea-a7e6-62bf4f9e548a

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Elliott suffers German court blow over Kabel Deutschland https://www.ft.com/content/0285292c-10fe-11ea-a7e6-62bf4f9e548a

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Malta’s moment of truth for a crusading journalist https://www.ft.com/content/6c0d2e0e-1134-11ea-a225-db2f231cfeae

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American Outdoor’s split highlights risks for gunmakers https://www.ft.com/content/e3ee9cde-0ac0-11ea-b2d6-9bf4d1957a67

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Clive James, writer, critic and broadcaster, 1939-2019 https://www.ft.com/content/985c7718-4f09-11e5-8642-453585f2cfcd

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Cleaning up Ukraine in the shadow of Trump https://www.ft.com/content/eb8e4004-1059-11ea-a7e6-62bf4f9e548a

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Jeremy Corbyn’s moment of truth looms large https://www.ft.com/content/80b6c686-1052-11ea-a7e6-62bf4f9e548a

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Arnaud Lagardère’s battle to retain grip on French empire https://www.ft.com/content/83015a6e-0ae9-11ea-b2d6-9bf4d1957a67

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Miami Republicans at odds with Trump on climate change https://www.ft.com/content/39df996a-0abf-11ea-b2d6-9bf4d1957a67

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Merkel warns Europe cannot defend itself without Nato https://www.ft.com/content/4a208660-10f8-11ea-a225-db2f231cfeae

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Brussels eyes easing bank rules to spur green loans https://www.ft.com/content/bddc3850-1054-11ea-a7e6-62bf4f9e548a

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Pentagon moves forward with Saudi defense mission https://www.washingtonpost.com/national-security/pentagon-moves-forward-with-saudi-defense-mission/2019/11/27/e1a36444-112a-11ea-b0fc-62cc38411ebb_story.html

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Netanyahu unleashes populist fury over indictments as some party members back away https://www.washingtonpost.com/world/middle_east/netanyahu-unleashes-populist-fury-over-indictments-as-party-members-back-away/2019/11/27/3109749c-10ea-11ea-924c-b34d09bbc948_story.html

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The strange tale of Japan’s prime minister, official documents and a very large shredder https://www.washingtonpost.com/world/asia-pacific/the-strange-tale-of-japans-prime-minister-official-documents-and-a-very-large-shredder/2019/11/27/f5cf5276-10e8-11ea-924c-b34d09bbc948_story.html

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The anti-indigenous politics that still fuels Latin America’s right https://www.washingtonpost.com/world/2019/11/27/anti-indigenous-politics-that-still-fuels-latin-americas-right/

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Afghan leader, U.S. envoy rebuke spy agency’s detention of activist reporting on sexual abuse https://www.washingtonpost.com/world/asia-pacific/afghan-leader-us-envoy-rebuke-kabuls-spy-agency-over-activists-detention/2019/11/27/7ccfaf12-10d7-11ea-924c-b34d09bbc948_story.html

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After the volcano, indigenous Guatemalans search for safer ground — in Guatemala, or the United States https://www.washingtonpost.com/world/2019/11/27/after-volcano-indigenous-guatemalans-search-safer-ground-guatemala-or-united-states/

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Trump official who suggested dropping nuclear bombs on Afghanistan now responsible for arms control issues https://www.washingtonpost.com/world/national-security/trump-official-who-suggested-dropping-nuclear-bombs-on-afghanistan-now-responsible-for-arms-control-issues/2019/11/27/235f2976-10af-11ea-a533-90a7becf7713_story.html

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A rope, tear gas and a fractured foot: How one Hong Kong protester escaped a besieged university https://www.washingtonpost.com/world/asia-pacific/a-rope-tear-gas-and-a-fractured-foot-how-one-hong-kong-protester-escaped-a-besieged-university/2019/11/27/ec301038-0bd5-11ea-8054-289aef6e38a3_story.html

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First target of Singapore’s ‘fake news’ law is Facebook post that alleged failed state investment in restaurant https://www.washingtonpost.com/world/2019/11/25/first-target-singapores-fake-news-law-is-facebook-post-that-alleged-failed-state-investment-salt-bae/

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Deadly measles outbreak hits children in Samoa after anti-vaccine fears https://www.washingtonpost.com/health/2019/11/26/deadly-measles-outbreak-hits-children-samoa-after-anti-vaccine-fears/

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Pope’s message of openness to refugees prompts social media backlash in Japan https://www.washingtonpost.com/world/popes-message-of-openness-to-refugees-prompts-social-media-backlash-in-japan/2019/11/27/8a48f21e-10fc-11ea-a533-90a7becf7713_story.html

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A Turkish dam is about to flood one of the oldest continuously settled places on Earth https://www.washingtonpost.com/world/middle_east/a-turkish-dam-is-about-to-flood-one-of-the-oldest-continuously-settled-places-on-earth/2019/11/26/26d327f2-0d48-11ea-8054-289aef6e38a3_story.html

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Britain’s chief rabbi blasts Labour Party for anti-Semitic ‘poison’ https://www.washingtonpost.com/world/europe/britains-chief-rabbi-blasts-labour-party-for-anti-semitic-poison/2019/11/26/d8c47e46-105b-11ea-924c-b34d09bbc948_story.html

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Saudi Arabia’s crackdown on dissent keeps going. Here are the latest arrests. https://www.washingtonpost.com/world/2019/11/26/saudi-arabias-crackdown-dissent-keeps-going-here-are-latest-arrests/

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As protests sweep Latin America, Bolsonaro warns Brazil: Don’t try it here https://www.washingtonpost.com/world/the_americas/as-protests-sweep-latin-america-bolsonaro-warns-brazil-dont-try-it-here/2019/11/26/a076ac24-105d-11ea-924c-b34d09bbc948_story.html

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graph view:


        
Show Nodes with Degree > 0:

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Language Processing Settings:

language logic: stop words:
 
merged nodes: unmerge
show as nodes: double brackets: categories as mentions:
discourse structure:
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×  ⁝⁝ 
Network Structure Insights
 
mind-viral immunity:
N/A
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stucture:
N/A
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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.

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Influence Distribution
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Topics Nodes in Top Topic Components Nodes in Top Comp
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Nodes Av Degree Density Weighed Betweenness
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Narrative Influence Propagation:
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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.
×  ⁝⁝ 
     
Main Topical Groups:

please, add your data to display the stats...
+     full stats   ?     show categories

The topics are 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:
please, add your data to display the stats...
+     Reveal Non-obvious   ?

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:
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.


Reset Graph   Export: Show Options
Action Advice:
N/A
Structural Gap
(ask a research question that would link these two topics):
N/A
Reveal the Gap   Generate a 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):
N/A
?

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
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.

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 as it allows us to better detect general patterns.

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
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Text Network Statistics:
Show Overlapping Nodes Only

⤓ Download as CSV  ⤓ Download an Excel File
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.
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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Enter a search query to analyze the Twitter discourse around this topic (last 7 days):

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