Emilie  Okumu

Emilie Okumu

1623191460

Telegram Network Visualization — Tracing Forwards and Mentions

Telegram reported a surge in active users after WhatsApp’s new terms of services raised privacy concerns. This article will explore avenues of getting public Telegram data without the need for account sign-ups, and the use of graph visualization to discover information flow between Telegram channels.

A tweet from Pavel Durov, founder of the Telegram Messenger, showing a surge in new account sign-ups.

Public Telegram channels are viewable without signing up for a Telegram account. There are many online Telegram archives that perform searches for Telegram channels. Let’s use this Telegram Explorer to search for cats, and pick the channel Kitty Cutie Pie, with channel ID pet_me_feed_me.

If the channel is a public one, there may be a Preview Channel option. This allows us to view the channel on a web browser without signing up for a Telegram account. Data such as profile picture, channel description, channel member count, message content, message posting time, and message view count are openly-available.

Channels are linked up through Forwards and Mentions. The screengrab on the bottom left shows a forwarded message from the Eduji Furchan channel, while the screengrab on the bottom right shows a mention of the _World_of_Puppy _channel.

Tracing out forwarded messages and mentions could help detect communities across Telegram channels and identify the source origin of content.

Prepping Data for Gephi

Gephi is a free online graph visualization tool that comes pre-packaged with layout algorithms and network metric calculations.

To ingest CSV files, Gephi requires data to contain the following column names, which are case sensitive.

  • Node.csv — Id, Label
  • Edge.csv — Source, Target

Other attributes may be added. For example, the column ‘Size’ (which represents that Telegram channel member count) is added to the node table. Load the CSV files under the Data Laboratory tab.

Perform the following transformations in the _Overview _Tab.

  • Layout: Choose an algorithm (e.g. _OpenOrd) _to arrange nodes in clusters.
  • Statistics: Run the _Modularity _function for cluster detection, and color the nodes based on the modularity class.
  • Node Labels: Turn on node labels, and play around with different fonts to display Chinese, Russian, Arabic characters, where necessary.
  • Node Size and Label Size: Scale node size and label size based on a calculated network metric (e.g. degree).
  • Readjustment: Run the Nooverlap and Lael Adjust algorithm so that nodes and labels do not overlap.

Head over to the _Preview _tab for the final aesthetic touch.

  • Opacity: Decreasing the opacity of nodes and edges helps improve the readability of labels.
  • Scaling: Label size and Edge thickness can be scaled.
  • Export: For a higher resolution screenshot, increase the pixels before doing a PNG export. You may have to increase Gephi memory here, to support exports of a higher pixel count.

Let us replicate these steps to analyze Telegram channels for a recent case.

Discovering Popular QAnon Sources

The QAnon community is active on Telegram, spreading conspiracy theories and distorting narrative pieces that may appear to be aligned with their ideologies.

#data-analysis #social-media #data-science #data-visualization #telegram

What is GEEK

Buddha Community

Telegram Network Visualization — Tracing Forwards and Mentions
Emilie  Okumu

Emilie Okumu

1623191460

Telegram Network Visualization — Tracing Forwards and Mentions

Telegram reported a surge in active users after WhatsApp’s new terms of services raised privacy concerns. This article will explore avenues of getting public Telegram data without the need for account sign-ups, and the use of graph visualization to discover information flow between Telegram channels.

A tweet from Pavel Durov, founder of the Telegram Messenger, showing a surge in new account sign-ups.

Public Telegram channels are viewable without signing up for a Telegram account. There are many online Telegram archives that perform searches for Telegram channels. Let’s use this Telegram Explorer to search for cats, and pick the channel Kitty Cutie Pie, with channel ID pet_me_feed_me.

If the channel is a public one, there may be a Preview Channel option. This allows us to view the channel on a web browser without signing up for a Telegram account. Data such as profile picture, channel description, channel member count, message content, message posting time, and message view count are openly-available.

Channels are linked up through Forwards and Mentions. The screengrab on the bottom left shows a forwarded message from the Eduji Furchan channel, while the screengrab on the bottom right shows a mention of the _World_of_Puppy _channel.

Tracing out forwarded messages and mentions could help detect communities across Telegram channels and identify the source origin of content.

Prepping Data for Gephi

Gephi is a free online graph visualization tool that comes pre-packaged with layout algorithms and network metric calculations.

To ingest CSV files, Gephi requires data to contain the following column names, which are case sensitive.

  • Node.csv — Id, Label
  • Edge.csv — Source, Target

Other attributes may be added. For example, the column ‘Size’ (which represents that Telegram channel member count) is added to the node table. Load the CSV files under the Data Laboratory tab.

Perform the following transformations in the _Overview _Tab.

  • Layout: Choose an algorithm (e.g. _OpenOrd) _to arrange nodes in clusters.
  • Statistics: Run the _Modularity _function for cluster detection, and color the nodes based on the modularity class.
  • Node Labels: Turn on node labels, and play around with different fonts to display Chinese, Russian, Arabic characters, where necessary.
  • Node Size and Label Size: Scale node size and label size based on a calculated network metric (e.g. degree).
  • Readjustment: Run the Nooverlap and Lael Adjust algorithm so that nodes and labels do not overlap.

Head over to the _Preview _tab for the final aesthetic touch.

  • Opacity: Decreasing the opacity of nodes and edges helps improve the readability of labels.
  • Scaling: Label size and Edge thickness can be scaled.
  • Export: For a higher resolution screenshot, increase the pixels before doing a PNG export. You may have to increase Gephi memory here, to support exports of a higher pixel count.

Let us replicate these steps to analyze Telegram channels for a recent case.

Discovering Popular QAnon Sources

The QAnon community is active on Telegram, spreading conspiracy theories and distorting narrative pieces that may appear to be aligned with their ideologies.

#data-analysis #social-media #data-science #data-visualization #telegram

Carmen  Grimes

Carmen Grimes

1595498460

Contact Tracing App: The Technology, Approach to fight COVID-19/Corona

As COVID-19 staggeringly lands blows to nations across the world, governments are considering ways to see their citizens through this pandemic. At the moment, a WHO situation report clocks the number of confirmed cases above two million along with more than one hundred thousand deaths. With vaccines dubbed as the best possible chance to tackle COVID-19 having no precise time frame of being ready, the talk is quickly shifting away to Contact Tracing Applications.

Contact tracing apps are digital solutions that use mobile technology to power the process of manual contact tracing. The apps follow a user’s movement, either by the use of Bluetooth technology, QR codes, or geo-location data while also tracking and keeping data from other user phones nearby. If one user gets diagnosed, the apps alert other users that they may have been exposed to the virus. As such, Contact Tracing Applications are being welcomed and perceived as an important approach to stem the spread of COVID-19 by providing a more accurate platform with data and information about affected individuals.

How Contact Tracing App Works

contact-tracing-app-devathon-

As mentioned above, contact tracing apps leverage mobile technology to trace cases of possible infection more accurately. But how exactly? Once installed and operative, the phone runs the app simultaneously with Bluetooth or location data to transmit signals with unique keys or IDs to phones in the designated range of connection. Similarly, the other phones with the app installed to detect and send back the signals.

For instance, if ‘Individual A’ has the app installed and goes outdoors to run some errands, they will interact with other individuals. In such a case, supposing all the other individuals had functional Contact Tracing Apps, each phone would exchange and store the contact data anonymously. It is important to note that the data collected only covers the app range distance to disregard irrelevant contacts and that their keys repeatedly change as individuals move. In any event that ‘Individual A’ tests positive for COVID-19 through confirmed tests, users who were previously within the proximity of ‘Individual A’ are alerted. Consequently, they are notified to check for symptoms, self-isolate, or get tested. Each time a person tests positive, the app notifies and advises the affected individuals.

In a nutshell, Contact Tracing Apps automate and supplement the traditional concept of tracing contacts to achieve extensive and realistic results in the least time possible.

What are the Benefits of Contact Tracing Apps?

Contract Tracing Apps are assets that offer indispensable solutions to health institutions and the public against COVID-19. There are several reasons why many governments are urging their citizens to use digital contact tracing apps to combat the spread of COVID-19. They include:

  1. The apps are more effective than manual tracing. While not perfect, their predictive algorithms frequently observe individuals detect new cases and analyze the probability one was infected. If one has contact with an asymptomatic individual, they are immediately notified and advised accordingly. Therefore, this saves time, energy, and resources that would have otherwise been overused.
  2. Contact tracing apps facilitate the relaxation of imposed restrictions or lockdowns. With a large number of infected people identified by the apps and put under surveillance, healthy citizens can be allowed to go about their duties. This may be a significant turning point to try and revive economies.
  3. Users’ private data is encrypted and secured. Even if you test positive, other users will only get notifications of possible infections. Your information is protected from both other users and developers of the app.
  4. They will increase the capacity to test and detect COVID-19 cases. With infected users alert, users who come in contact with affected persons come forward to be tested and treated with a higher recovery chance.

Future of Contact Tracing Apps?

Currently, the role of contact tracing apps is limited to accurately identifying infected individuals and their contacts as well as facilitating a quicker response to the Covid-19 threat.

Beyond that, the use of contact tracing apps is projected to take a different turn. One key area bound to change is how people’s privacy is handled. Tech institutions are under growing pressure to devise ways to develop privacy-preserving Contact Tracing Apps.

This will earn the users-trust, which is a pillar for these apps to help contain the disease. Technically, the technology will also have to improve drastically. The apps will have to seamlessly integrate with the user’s phone lifestyle causing minimal or no interference. With most applications having an open-source code, Artificial Intelligence, Beacon Technology, and Big Data solutions will be increasingly harnessed to power and improve them. The apps may also cut across various types of industries apart from health institutions.

How Can It Help to Trace COVID-19 and Reduce the Spread of the Virus?

contact-tracing-app-devathon-3

Contact Tracing Apps will effectively help stem lowering the cases of COVID-19. By using the apps, officials are able to monitor high-risk individuals easily. Also, should any new case arise, both users and health officials get notified they will swiftly act to trace, test, or isolate infected individuals.

Unlike traditional contact tracing, which may not get all contacts, these apps ensure that once Covid-19 cases are detected, they are all treated early, and those other individuals are not exposed to the infection. They also ward off users from high-risk areas. In the long run, they help break the COVID-19 chain by preventing further spread. Illustratively, an online publication by  CNBC states that more than 500,000 using a Singapore-registered mobile number downloaded the TraceTogether app within the first 24 hours of its launch. Subsequently, together with other government efforts, Singapore has since lowered the infection rate and eased restrictions.

If Contact Tracing Apps are implemented and used alongside other policies, we may as well be a few steps way to curbing this virus.

#android app #ios app #mobile app development #news #technology #contact tracing #contact tracing app #contact tracing app approach #contact tracing app technology #contact tracing coronavirus #contact tracing process #corona virus detecting app #corona virus tracing app #corona virus tracker #corona virus tracker live

What is Trace Network (TRACE) | What is Trace Network token | What is TRACE token

In this article, we’ll discuss information about the Trace Network project and TRACE token

Trace Network is a unique business model that is packaged as an enterprise-grade, proof-of-stake, permissionless protocol for supply chain, data management, trade settlement and financing powered by DeFi and NFTs.

Why Trace Network

Industry 4.0 solutions did leave few areas uncovered. Its time for Industry 5.0

Counterfeit & Invisible Merchandise

Disconnected Data Silos

Expensive & Cumbersome Cashflow Financing Options

Benefits of Trace Network

Trace Network makes businesses Sustainable by enabling core components like Transparency, Trust and Efficiency to achieve complete digital transformation.

Real time merchandise traceability

Fast and efficient data transfer

Smart contract enabled process provenance

Efficient working capital financing options

Real time trade settlement

Unlocking dead liquidity enabling financial mileage

Advantages

Trace Network is build by people from industry active in emerging tech for over two decades hence understand the need, complexity and solution for preparing businesses for new era.

50+ man years of Experience

50+ Enterprise Technology company Relationships

Global Enterprise Reach

Learned pool of Advisers

Trace Tokenomics

Trace Network is an enterprise grade decentralized finance protocol harnessing the capabilities of composable smart contracts, permission-less financing options powered by DeFi and NFT based unique merchandise identification solutions to unlock the billions of dollars’ worth of business potential otherwise undermined due to poor merchandise inventory & ownership management, costlier trade financing & banking options, and perennial inefficiencies in par diem business transactions.

Trace Network would utilize unique capabilities of DLTs, DeFi & NFTs to empower participants of the Trace ecosystem to interact and share data which are required to enforce traceability, distribution channel stock visibility & above all, efficient working capital financing options for more efficient trade practices & business management.

Some of the core functions to help the protocol standout and spearhead the adoption torch are:

❏ NFT based on-chain merchandise Identity Management

❏ On-Chain integration & settlement of business transactions across business networks

❏ DeFi based on-chain liquidity & trade financing

TRACE; The Governance Token empowering the Trace Network ecosystem

To achieve the vision & mission as described above, we are proud to introduce $TRACE as the governance token. $TRACE is an ERC20 standard token with inbuilt governance & community participation capabilities for a more participative & vibrant community engagement in decision making.

Trace Distribution

100,000,000 TRACE shall ever exist, hence the total supply.

30,620,000 TRACE are reserved for community incentives, business development & ecosystem promotion. Out of this 20,620,000 TRACE are allocated separately in an ecosystem & business development fund, to be unlocked over a period of 24 months. Remaining 10,000,000 TRACE to be used for community incentivization for early adoption of the protocol, which will be unlocked over a period of 18 months.

16,380,000 TRACE are allocated to early backers & strategic investors, vested for a period upto 15 months.

500,000 TRACE are allocated for public sale.

10,000,000 TRACE are allocated to existing & future advisors, vested for a period upto 15 months. 5% of allocated TRACE will be unlocked on TGE and remaining to be vested for the mentioned period as above.

20,000,000 TRACE are allocated to founders & the team, subject to 18 Months vesting. 10% of allocated TRACE will be unlocked on month 6 and then unlocked daily for the vested period as mentioned.

20,000,000 TRACE are reserved for foundation and meant for product development & business expansion, strategic investment and are subjected to 24 months vesting. 10% of allocated TRACE will be unlocked on month 9 and then distributed daily till 24 months in total.

2,500,000 TRACE are allocated for the liquidity provision fund.

Trace Token Utility

Governance

TRACE is the governance token and empowers network users with governance control over the protocol. Network users & holders shall be able to run protocol on a day to day basis and participate in various decisions accordingly.

Protocol incentivization

TRACE would be distributed as a reward to network participants through various incentivization mechanisms from time to time.

Protocol participation

TRACE token is the fuel of the network and ecosystem which makes it mandatory for network participants to use for transactions & participate in operations of the protocol.

Staking rewards

A major portion of TRACE’s total supply is to be distributed among network users and therefore, TRACE will be used to incentivize staking on the network.

Interoperability & cross-chain settlement

TRACE will be used as a unit of settlement for all cross-chain settlement and a reconciliation unit for multi-chain interaction including inter & intra-chain transactions.

NFT Minting & Settlement

TRACE will be used as a base token to mint, acquire NFTs, and for the settlement of minted NFTs over the network and ecosystem. TRACE will be the preferred form of payment available for token issuance, transfer, and destruction.

Trade & Commerce

TRACE will act as a settlement & accounting unit for the exchange of value among different enterprises on the network. TRACE will act as a base layer of settlement & stability unit for all business transactions empowered by proprietary white label algorithmic stable coins.

How and Where to Buy TRACE token?

You will have to first buy one of the major cryptocurrencies, usually either Bitcoin (BTC), Ethereum (ETH), Tether (USDT), Binance (BNB)…

We will use Binance Exchange here as it is one of the largest crypto exchanges that accept fiat deposits.

Binance is a popular cryptocurrency exchange which was started in China but then moved their headquarters to the crypto-friendly Island of Malta in the EU. Binance is popular for its crypto to crypto exchange services. Binance exploded onto the scene in the mania of 2017 and has since gone on to become the top crypto exchange in the world.

Once you finished the KYC process. You will be asked to add a payment method. Here you can either choose to provide a credit/debit card or use a bank transfer, and buy one of the major cryptocurrencies, usually either Bitcoin (BTC), Ethereum (ETH), Tether (USDT), Binance (BNB)…

SIGN UP ON BINANCE

Step by Step Guide : What is Binance | How to Create an account on Binance (Updated 2021)

Next step - Transfer your cryptos to an Altcoin Exchange

Once finished you will then need to make a BTC/ETH/USDT/BNB deposit to the exchange from Binance depending on the available market pairs. After the deposit is confirmed you may then purchase TRACE from the IDO exchange:** SushiSwap’s MISO Launchpad**.

The top exchange for trading in TRACE token is currently 

Find more information TRACE

WebsiteWhitepaperSocial ChannelSocial Channel 2Message Board

🔺DISCLAIMER: The Information in the post isn’t financial advice, is intended FOR GENERAL INFORMATION PURPOSES ONLY. Trading Cryptocurrency is VERY risky. Make sure you understand these risks and that you are responsible for what you do with your money.

🔥 If you’re a beginner. I believe the article below will be useful to you ☞ What You Should Know Before Investing in Cryptocurrency - For Beginner

⭐ ⭐ ⭐The project is of interest to the community. Join to Get free ‘GEEK coin’ (GEEKCASH coin)!

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Thank for visiting and reading this article! Please don’t forget to leave a like, comment and share!

#blockchain #bitcoin #trace #trace network

Marlon  Boyle

Marlon Boyle

1594312560

Autonomous Driving Network (ADN) On Its Way

Talking about inspiration in the networking industry, nothing more than Autonomous Driving Network (ADN). You may hear about this and wondering what this is about, and does it have anything to do with autonomous driving vehicles? Your guess is right; the ADN concept is derived from or inspired by the rapid development of the autonomous driving car in recent years.

Image for post

Driverless Car of the Future, the advertisement for “America’s Electric Light and Power Companies,” Saturday Evening Post, the 1950s.

The vision of autonomous driving has been around for more than 70 years. But engineers continuously make attempts to achieve the idea without too much success. The concept stayed as a fiction for a long time. In 2004, the US Defense Advanced Research Projects Administration (DARPA) organized the Grand Challenge for autonomous vehicles for teams to compete for the grand prize of $1 million. I remembered watching TV and saw those competing vehicles, behaved like driven by drunk man, had a really tough time to drive by itself. I thought that autonomous driving vision would still have a long way to go. To my surprise, the next year, 2005, Stanford University’s vehicles autonomously drove 131 miles in California’s Mojave desert without a scratch and took the $1 million Grand Challenge prize. How was that possible? Later I learned that the secret ingredient to make this possible was using the latest ML (Machine Learning) enabled AI (Artificial Intelligent ) technology.

Since then, AI technologies advanced rapidly and been implemented in all verticals. Around the 2016 time frame, the concept of Autonomous Driving Network started to emerge by combining AI and network to achieve network operational autonomy. The automation concept is nothing new in the networking industry; network operations are continually being automated here and there. But this time, ADN is beyond automating mundane tasks; it reaches a whole new level. With the help of AI technologies and other critical ingredients advancement like SDN (Software Defined Network), autonomous networking has a great chance from a vision to future reality.

In this article, we will examine some critical components of the ADN, current landscape, and factors that are important for ADN to be a success.

The Vision

At the current stage, there are different terminologies to describe ADN vision by various organizations.
Image for post

Even though slightly different terminologies, the industry is moving towards some common terms and consensus called autonomous networks, e.g. TMF, ETSI, ITU-T, GSMA. The core vision includes business and network aspects. The autonomous network delivers the “hyper-loop” from business requirements all the way to network and device layers.

On the network layer, it contains the below critical aspects:

  • Intent-Driven: Understand the operator’s business intent and automatically translate it into necessary network operations. The operation can be a one-time operation like disconnect a connection service or continuous operations like maintaining a specified SLA (Service Level Agreement) at the all-time.
  • **Self-Discover: **Automatically discover hardware/software changes in the network and populate the changes to the necessary subsystems to maintain always-sync state.
  • **Self-Config/Self-Organize: **Whenever network changes happen, automatically configure corresponding hardware/software parameters such that the network is at the pre-defined target states.
  • **Self-Monitor: **Constantly monitor networks/services operation states and health conditions automatically.
  • Auto-Detect: Detect network faults, abnormalities, and intrusions automatically.
  • **Self-Diagnose: **Automatically conduct an inference process to figure out the root causes of issues.
  • **Self-Healing: **Automatically take necessary actions to address issues and bring the networks/services back to the desired state.
  • **Self-Report: **Automatically communicate with its environment and exchange necessary information.
  • Automated common operational scenarios: Automatically perform operations like network planning, customer and service onboarding, network change management.

On top of those, these capabilities need to be across multiple services, multiple domains, and the entire lifecycle(TMF, 2019).

No doubt, this is the most ambitious goal that the networking industry has ever aimed at. It has been described as the “end-state” and“ultimate goal” of networking evolution. This is not just a vision on PPT, the networking industry already on the move toward the goal.

David Wang, Huawei’s Executive Director of the Board and President of Products & Solutions, said in his 2018 Ultra-Broadband Forum(UBBF) keynote speech. (David W. 2018):

“In a fully connected and intelligent era, autonomous driving is becoming a reality. Industries like automotive, aerospace, and manufacturing are modernizing and renewing themselves by introducing autonomous technologies. However, the telecom sector is facing a major structural problem: Networks are growing year by year, but OPEX is growing faster than revenue. What’s more, it takes 100 times more effort for telecom operators to maintain their networks than OTT players. Therefore, it’s imperative that telecom operators build autonomous driving networks.”

Juniper CEO Rami Rahim said in his keynote at the company’s virtual AI event: (CRN, 2020)

“The goal now is a self-driving network. The call to action is to embrace the change. We can all benefit from putting more time into higher-layer activities, like keeping distributors out of the business. The future, I truly believe, is about getting the network out of the way. It is time for the infrastructure to take a back seat to the self-driving network.”

Is This Vision Achievable?

If you asked me this question 15 years ago, my answer would be “no chance” as I could not imagine an autonomous driving vehicle was possible then. But now, the vision is not far-fetch anymore not only because of ML/AI technology rapid advancement but other key building blocks are made significant progress, just name a few key building blocks:

  • software-defined networking (SDN) control
  • industry-standard models and open APIs
  • Real-time analytics/telemetry
  • big data processing
  • cross-domain orchestration
  • programmable infrastructure
  • cloud-native virtualized network functions (VNF)
  • DevOps agile development process
  • everything-as-service design paradigm
  • intelligent process automation
  • edge computing
  • cloud infrastructure
  • programing paradigm suitable for building an autonomous system . i.e., teleo-reactive programs, which is a set of reactive rules that continuously sense the environment and trigger actions whose continuous execution eventually leads the system to satisfy a goal. (Nils Nilsson, 1996)
  • open-source solutions

#network-automation #autonomous-network #ai-in-network #self-driving-network #neural-networks

Arvel  Parker

Arvel Parker

1591177440

Visual Analytics and Advanced Data Visualization

Visual Analytics is the scientific visualization to emerge an idea to present data in such a way so that it could be easily determined by anyone.

It gives an idea to the human mind to directly interact with interactive visuals which could help in making decisions easy and fast.

Visual Analytics basically breaks the complex data in a simple way.

The human brain is fast and is built to process things faster. So Data visualization provides its way to make things easy for students, researchers, mathematicians, scientists e

#blogs #data visualization #business analytics #data visualization techniques #visual analytics #visualizing ml models