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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.

Ethereum Co-Founder Says He Doesn’t Fear The $DOGE - Why fear your friend I say? 🐕💰🚀 https://twitter.com/kokid951/status/1402064760464543757

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Final Bitcoin $BTC chart and comment in June. I'll check back in July https://t.co/bWdygg9b8x https://twitter.com/PeterLBrandt/status/1402067888324988930

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🤔 If they touch your _______ it's over. $BTC $ETH $DOT https://twitter.com/HuobiGlobal/status/1402073329444458500

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When are we buying the dip? $BTC $ETH $DOT https://twitter.com/HuobiGlobal/status/1402103086148210689

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@Poloniex will support the 2-YEAR airdrop plan initiated by APENFT $NFT @apenftorg 🎉 $BTC, $ETH, $TUSD, $TRX, $BTT $JST holders will get the chance to earn the airdrop. 9,999,900,000,000 NFT will be distributed initially 💰 Snapshot on 6/10/21 Details https://t.co/JBdsCfW6iJ https://t.co/1ROkD1skbT https://twitter.com/Poloniex/status/1402118380581130243

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$ETH isn’t MySpace. https://twitter.com/davidgokhshtein/status/1402155472157818884

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Holding $BUSD $USDT $USDC $BTC $ETH ? Use https://t.co/zi257M2vYa and put them into work on #BinanceSmartChain https://t.co/SLK2UnOean https://twitter.com/BinanceChain/status/1402192893322829826

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Have you joined our biggest social media giveaway (to date)? #BybitBonanzaGiveaway – with prizes worth up to $50,000 in $BTC! 🤑 Learn More ➡️ https://t.co/o7eAsvzRN5 https://t.co/ONZyODlvGe https://twitter.com/Bybit_Official/status/1402196882210836481

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Listing at Bitstamp is at an all-time high: $USDT, $COMP and $GRT are coming to Bitstamp with zero trading fees until the end of September! More info, including a full list of pairs and launch schedule: https://t.co/86e2S6u7Ka https://twitter.com/Bitstamp/status/1402200278233931777

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✊🏻 Calling all $DOGE @dogecoin $SHIB @shiba_coin & $OKB @OKEx supporters! 🗳 Join Prize Token Vote: #Hodl & Vote to share a prize pool of $555 ✅ Follow @OKEx & our English Telegram group: https://t.co/ivGn3zZkMS ✅Register your entry: https://t.co/dZDFIk8WJg https://t.co/FJeDObp5xr https://twitter.com/OKEx/status/1402203929870585856

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22,550 $BTC removed from crypto exchanges yesterday. That's a lot of supply being removed from the active market - the most in a day this entire year. https://t.co/W7N6TWbQFt https://twitter.com/scottmelker/status/1402207296441171970

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A gentle reminder... June 8, 2020: $BTC = $9,727 $ETH = $243 $DOGE = $0.0025 June 8, 2021: $BTC = $33,486 $ETH = $2,516 $DOGE = $0.34 https://twitter.com/Okcoin/status/1402408219176161280

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hey @GameStop I’m a shareholder so you gotta listen please add $DOGE to your online payment options and I will start buying preowned stuff from you, and maybe even get the game insurance thing https://twitter.com/BillyM2k/status/1402607223071670284

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I can see $XRP being next to be accepted as a legal tender. https://twitter.com/davidgokhshtein/status/1402684492926664711

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$DOGE being mentioned in Senate hearings is pretty cool to hear. https://twitter.com/davidgokhshtein/status/1403339830663290882

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I don’t understand how smart progressives like @SenWarren don’t see how crypto and $BTC shifts power away from rent taking organizations like banks (who she is always fighting) to the people. I am glad to come to DC or Boston to explain. https://t.co/2PgKe5y9sV https://twitter.com/novogratz/status/1403678759576911872

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Yooo love it. DOGE for UFC $DOGE #DOGE https://t.co/irtY71a1cX https://twitter.com/christinebarnum/status/1403883694230687745

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#Bitcoin jumped above $39,000 after @elonmusk said Tesla would resume transactions with the cryptocurrency when mining is done with more clean energy https://t.co/sPOulu0yFW $BTC $TSLA https://t.co/Tb5ekBdmxh https://twitter.com/crypto/status/1404243286802501637

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#Dogecoin on Billboards $DOGE on the @ufc mat #Doge Ads in Times Square 👏🏻👏🏻👏🏻No Joke DogeCoin is Unstoppable Now🐕🔥🚀 https://twitter.com/kokid951/status/1404293814504722433

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$DOGE .32 https://twitter.com/christinebarnum/status/1404326926152441856

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Due to a third-party service anomaly, the $USDT price deviated from its market value & some Nexo clients’ balances were incorrectly liquidated. All incorrect liquidations will be reversed & your wallets’ balances will be restored shortly. We apologize for any inconvenience. https://twitter.com/NexoFinance/status/1404375582771712004

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40K all day. $BTC https://twitter.com/scottmelker/status/1404433146217648133

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$BTC is soaring over $40K this morning 🚀 Earn up 6.25% interest on #Bitcoin when you #HODL on #Voyager. Buy and trade #BTC now: https://t.co/OSytUm4Nr2 https://t.co/1JQvN2RJP8 https://twitter.com/investvoyager/status/1404438040836182020

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$DOGE .33 https://twitter.com/christinebarnum/status/1404443465740537865

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A morning pump 💪 $btc https://twitter.com/AmandaCerny/status/1404447778437279754

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Loaded up on more $Doge, $Matic $Ankr and $Amp yesterday. Also bought Harmony $One too.. https://twitter.com/Lilmook4real/status/1404454272419483650

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Good morning. Some of you know that I sold 1/2 my #Bitcoin in mid March, I transferred 5 $BTC to $DOGE & $ADA . Doge average: $.125 ADA average: $.89 BTC average: $4,000 Nice to see BTC hit $40k again Doge & ETH will climb back up again. Be patient & #HODL Diamond Hands gang! https://twitter.com/BENBALLER/status/1404487351863169034

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LET'S GO: We are happy to share that we have just released a brand new version of the #Cardano node, version, #AlonzoBlue 2.0 to the testnet. This is an important milestone – thanks and congrats to all the #AlonzoBlue team for the hard work to bring us here 🙏 #Cardano $ADA 1/4 https://t.co/slcd1TgQtl https://twitter.com/InputOutputHK/status/1404534598709780490

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06/14/21 UPDATE: Net Assets Under Management, Holdings per Share, and Market Price per Share for our Investment Products. Total AUM: $35.5 billion $BTC $BCH $ETH $ETC $ZEN $LTC $XLM $ZEC $BAT $LINK $MANA $FIL $LPT https://t.co/DaGRDu6A6L https://twitter.com/Grayscale/status/1404540165431910404

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Elon and Cuban repping $DOGE is great for the space. https://twitter.com/davidgokhshtein/status/1404562348275294209

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Goldman Sachs is moving beyond the world of #Bitcoin and expanding into #Ether https://t.co/HFF3SmpRYZ More on @crypto: https://t.co/LYphXLEzpH $ETH $GS https://t.co/gCrv4nZuTy https://twitter.com/crypto/status/1404624283247185920

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Fund4 voting is now underway for #ProjectCatalyst!! 💪 You have until 25th June 11:00 UTC to vote on the projects you want to support & make your voice heard. Vote for one project or all – choice is yours. Here is all you need to know: https://t.co/Uhm1vTuGSX #Cardano $ADA https://t.co/wyJo31wNFT https://twitter.com/InputOutputHK/status/1404779480057581568

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" $SHIB is better than $DOGE because it got listed on Coinbase Pro faster!” WTF? https://twitter.com/davidgokhshtein/status/1404867812695359488

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Last time I looked, the $DOGE isn’t trying to kill any other #cryptocurrency. https://twitter.com/davidgokhshtein/status/1404885438196862986

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Another strong buy coming in! Many more will soon follow! Bought 24241000000000 $FEG for 75.952 $ETH 🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢🟢 https://twitter.com/FEGtoken/status/1404910343936163843

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network diversity:
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Network Structure Insights
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diversity:
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  stucture:
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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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Topics Nodes in Top Topic Components Nodes in Top Comp
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Nodes Av Degree Density Weighed Betweenness
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Degree Distribution:
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distribution (based on kolmogorov-smirnov test) ?
narrative fractality: | alpha exponent: (based on Detrended Fluctuation Analysis of influence) ?
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.
We plot the narrative as a time series of influence (using the words' betweenness score). We then apply detrended fluctuation analysis to identify the fractality of this time series (using alpha exponent, closely related to Hurst exponent): uniform (pulsating | alpha <= 0.65), regular (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 and plurality, the narrative should be close to "fractal". For poetry — "complex". For ideological texts — "uniform".
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Main Topical Groups:

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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 and are given a distinct color.
Most Influential Elements:
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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:
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Action Advice:
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Structural Gap
(ask a research question that would link these two topics):
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Reveal the Gap   ?
 
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
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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
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Evolution of Topics
(frequency over time)

 
Main Topics
(according to Latent Dirichlet Allocation):
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Most Influential Words
(main topics and words according to LDA):
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LDA works only for English-language texts at the moment. More support is coming soon, subscribe @noduslabs to be informed.

Network Statistics:
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Top Relations / Bigrams
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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).
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