The document summarizes a weekly meeting of an informatics student group discussing their work on Twitter Transparency Project datasets. They found some datasets used different languages and hashtags to spread content. Most fake COVID news was early 2020 with few false stories since on Chinese social media. They cleaned data by changing separators and removing line breaks and special characters, processing over 50GB of data. Sentiment analysis tools worked on English data but showed abnormal results on Chinese data. They have datasets on real, fake and disinformation COVID news in Chinese and English and will use existing data to train judgment models.
Network Relationships and Job Changes of Software Developers at Sunbelt 2016Dawn Foster
This presentation looks at job changes of software developers within an open source software community using
relational predictors of job change activity to model the actions of the actors involved. Interactions with other actors
on mailing lists and in software contributions will be used as predictors.
Open source software is developed in the open where anyone can view the source code and anyone with the knowledge
to do so can contribute to the project. Because people from around the world work on these projects together using
online tools with publicly accessible interactions between people, it is a relevant setting for studying job changes
using Social Network Analysis to understand and model the network relationships between individuals both before
and after a job change.
This eBook is a starting point for those who just started to learn c Python programming. The
backbone of any programming, which is the data structure
and components such as strings, list, etc., have been
illustrated with many examples and enough practices to
instill a level of self-confidence in the reader.
Detailed description of big data, with the characteristics of it. What are the limitations of the traditional systems? Where we are using big data? And also the applications of big data.
Network Relationships and Job Changes of Software Developers at Sunbelt 2016Dawn Foster
This presentation looks at job changes of software developers within an open source software community using
relational predictors of job change activity to model the actions of the actors involved. Interactions with other actors
on mailing lists and in software contributions will be used as predictors.
Open source software is developed in the open where anyone can view the source code and anyone with the knowledge
to do so can contribute to the project. Because people from around the world work on these projects together using
online tools with publicly accessible interactions between people, it is a relevant setting for studying job changes
using Social Network Analysis to understand and model the network relationships between individuals both before
and after a job change.
This eBook is a starting point for those who just started to learn c Python programming. The
backbone of any programming, which is the data structure
and components such as strings, list, etc., have been
illustrated with many examples and enough practices to
instill a level of self-confidence in the reader.
Detailed description of big data, with the characteristics of it. What are the limitations of the traditional systems? Where we are using big data? And also the applications of big data.
Big Data LDN 2018: ENABLING DATA-DRIVEN DECISIONS WITH AUTOMATED INSIGHTSMatt Stubbs
Date: 13th November 2018
Location: Customer Experience Theatre
Time: 11:50 - 12:20
Speaker: Charlotte Emms
Organisation: seenit
About: How do you get your colleagues interested in the power of data? Taking you through Seenit’s journey using Couchbase's NoSQL database to create a regular, fully automated update in an easily digestible format.
Are you responsible for developing satellite on-board software? Are you the Dutch government and you have to efficiently implement the public benefits law? Are you a healthcare startup, developing companion apps that help patients through a treatment? Are you an insurance company struggling to create new, and evolve existing products quickly to keep up with the market? These are all examples of organisations who have built their own domain-specific programming language to streamline the development of applications that have a non-trivial algorithmic core. All have built their languages with Jetbrains MPS, an open source language development tool optimized for ecosystems of collaborating languages with mixed graphical, textual, tabular and mathematical notations. This talk has four parts. I start by motivating the need for DSLs based on real-world examples, including the ones above. I will then present a few high-level design practices that guide our language development work. Third, I will develop a simple language extension to give you a feel for how MPS works. And finally, I will point you to things you can read to get you started with your own language development practice.
What is python language and How it works.pdfchanduvarma019
Advanced Btech CSE Academic IEEE mini Python Projects in Hyderabad for Final Year Students of Engineering. Computer Science and Engineering latest mini Python Projects."
As part of the final BETTER Hackathon, project partners prepared 4 hackathon exercises. Fraunhofer IAIS organised this exercise in conjunction with external partner MKLab ITI-CERTH (EOPEN project). This step-by-step exercise featured the setup of local Docker images on Linux OS featuring Dcoker Compose and (pre-installed) Python, SANSA, Hadoop, Apache Spark and Apache Zeppelin. It featured semantic transformation and and the use of SANSA (Scalable Semantic Analytics Stack - http://sansa-stack.net/) libraries on a sample of tweets ahead of geo-clustering.
Project website (Hackathon information): https://www.ec-better.eu/pages/2nd-hackathon
Github repository: https://github.com/ec-better/hackathon-2020-semanticgeoclustering
USING MACHINE LEARNING TO BUILD A SEMI-INTELLIGENT BOT ecij
Nowadays, real-time systems and intelligent systems offer more and more control interface based on voice recognition or human language recognition. Robots and drones will soon be mainly controlled by voice. Other robots will integrate bots to interact with their users, this can be useful both in industry and entertainment. At first, researchers were digging on the side of "ontology reasoning". Given all the technical constraints brought by the treatment of ontologies, an interesting solution has emerged in last years: the construction of a model based on machine learning to connect a human language to a knowledge
base (based for example on RDF). We present in this paper our contribution to build a bot that could be used on real-time systems and drones/robots, using recent machine learning technologies.
USING MACHINE LEARNING TO BUILD A SEMI-INTELLIGENT BOT ecij
Nowadays, real-time systems and intelligent systems offer more and more control interface based on voice
recognition or human language recognition. Robots and drones will soon be mainly controlled by voice.
Other robots will integrate bots to interact with their users, this can be useful both in industry and
entertainment. At first, researchers were digging on the side of "ontology reasoning". Given all the
technical constraints brought by the treatment of ontologies, an interesting solution has emerged in last
years: the construction of a model based on machine learning to connect a human language to a knowledge
base (based for example on RDF). We present in this paper our contribution to build a bot that could be
used on real-time systems and drones/robots, using recent machine learning technologies.
Snowplow at the heart of Busuu's data & analytics infrastructureGiuseppe Gaviani
Presented at Snowplow London Meetup, 8 February 2017
Bruce Pannaman, data scientist at Busuu, talked about why they are using Snowplow to validate and enrich data, enable one source of truth across different data sources, cope with peaks and troughs in the data stream, and easily integrate with third party systems such as Intercom, a customer messaging platform. One of Busuu’s future projects is to load multiple A/B tests into the apps and monitor their results in real time.
Big Data LDN 2018: ENABLING DATA-DRIVEN DECISIONS WITH AUTOMATED INSIGHTSMatt Stubbs
Date: 13th November 2018
Location: Customer Experience Theatre
Time: 11:50 - 12:20
Speaker: Charlotte Emms
Organisation: seenit
About: How do you get your colleagues interested in the power of data? Taking you through Seenit’s journey using Couchbase's NoSQL database to create a regular, fully automated update in an easily digestible format.
Are you responsible for developing satellite on-board software? Are you the Dutch government and you have to efficiently implement the public benefits law? Are you a healthcare startup, developing companion apps that help patients through a treatment? Are you an insurance company struggling to create new, and evolve existing products quickly to keep up with the market? These are all examples of organisations who have built their own domain-specific programming language to streamline the development of applications that have a non-trivial algorithmic core. All have built their languages with Jetbrains MPS, an open source language development tool optimized for ecosystems of collaborating languages with mixed graphical, textual, tabular and mathematical notations. This talk has four parts. I start by motivating the need for DSLs based on real-world examples, including the ones above. I will then present a few high-level design practices that guide our language development work. Third, I will develop a simple language extension to give you a feel for how MPS works. And finally, I will point you to things you can read to get you started with your own language development practice.
What is python language and How it works.pdfchanduvarma019
Advanced Btech CSE Academic IEEE mini Python Projects in Hyderabad for Final Year Students of Engineering. Computer Science and Engineering latest mini Python Projects."
As part of the final BETTER Hackathon, project partners prepared 4 hackathon exercises. Fraunhofer IAIS organised this exercise in conjunction with external partner MKLab ITI-CERTH (EOPEN project). This step-by-step exercise featured the setup of local Docker images on Linux OS featuring Dcoker Compose and (pre-installed) Python, SANSA, Hadoop, Apache Spark and Apache Zeppelin. It featured semantic transformation and and the use of SANSA (Scalable Semantic Analytics Stack - http://sansa-stack.net/) libraries on a sample of tweets ahead of geo-clustering.
Project website (Hackathon information): https://www.ec-better.eu/pages/2nd-hackathon
Github repository: https://github.com/ec-better/hackathon-2020-semanticgeoclustering
USING MACHINE LEARNING TO BUILD A SEMI-INTELLIGENT BOT ecij
Nowadays, real-time systems and intelligent systems offer more and more control interface based on voice recognition or human language recognition. Robots and drones will soon be mainly controlled by voice. Other robots will integrate bots to interact with their users, this can be useful both in industry and entertainment. At first, researchers were digging on the side of "ontology reasoning". Given all the technical constraints brought by the treatment of ontologies, an interesting solution has emerged in last years: the construction of a model based on machine learning to connect a human language to a knowledge
base (based for example on RDF). We present in this paper our contribution to build a bot that could be used on real-time systems and drones/robots, using recent machine learning technologies.
USING MACHINE LEARNING TO BUILD A SEMI-INTELLIGENT BOT ecij
Nowadays, real-time systems and intelligent systems offer more and more control interface based on voice
recognition or human language recognition. Robots and drones will soon be mainly controlled by voice.
Other robots will integrate bots to interact with their users, this can be useful both in industry and
entertainment. At first, researchers were digging on the side of "ontology reasoning". Given all the
technical constraints brought by the treatment of ontologies, an interesting solution has emerged in last
years: the construction of a model based on machine learning to connect a human language to a knowledge
base (based for example on RDF). We present in this paper our contribution to build a bot that could be
used on real-time systems and drones/robots, using recent machine learning technologies.
Snowplow at the heart of Busuu's data & analytics infrastructureGiuseppe Gaviani
Presented at Snowplow London Meetup, 8 February 2017
Bruce Pannaman, data scientist at Busuu, talked about why they are using Snowplow to validate and enrich data, enable one source of truth across different data sources, cope with peaks and troughs in the data stream, and easily integrate with third party systems such as Intercom, a customer messaging platform. One of Busuu’s future projects is to load multiple A/B tests into the apps and monitor their results in real time.
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
5. Interesting Found
I found out that most of the fake news about
Covid is happening in the first quarter of 2020
Since then there have been very few false news
stories about local outbreaks on Chinese social
media
6. Data Cleaning - SBS Ready Format
Works:
- Change separator from ‘,’ to ‘|’
- Remove ‘|’ in text column
- Remove line brakes
- 50GB+ data on Python
- .csv .json .zst
- UTF-8 ready
Not works:
- Output exact 30MB size on each file
- Separated file on seperate language
- 1,048,576+ rows on Excel
- 10GB+ data on Excel
12. A dataset of disinformation about COVID-19——English
13. Questions
1. What is the relationship between sentiment analysis of data and
our project？
2. With the results of the sentiment analysis, what do we do next？
1. Use existing data to train and build judgment models.
Future Planning
