This document summarizes Twitter usage statistics from June 2009. It finds that over half of Twitter accounts are inactive, having tweeted few times and having few followers/followings. For active users, it reports they tweet almost daily and have over 100 tweets total. Location data shows Twitter is popular in major English-speaking cities. The document was compiled using data from over 4.5 million Twitter profiles on Twitter Grader.
The state of the Twittersphere in February 2011Kathryn Corrick
An overview of Twitter in February 2011 using statistics, tools and freely available information.
Also see: http://kathryncorrick.co.uk/2011/02/17/the-state-of-the-twittersphere-in-february-2011/
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The overview is a snapshot of the total conversation throughout the month of September 2016. This includes a timeline of volume, from which we can determine whether conversation has increased, decreased or stagnated. We can also pull summaries of the most commonly discussed topics.
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An overview of Twitter in February 2011 using statistics, tools and freely available information.
Also see: http://kathryncorrick.co.uk/2011/02/17/the-state-of-the-twittersphere-in-february-2011/
Uk Labour Party - September 2016 AnalysisJames Shier
The overview is a snapshot of the total conversation throughout the month of September 2016. This includes a timeline of volume, from which we can determine whether conversation has increased, decreased or stagnated. We can also pull summaries of the most commonly discussed topics.
This study reviewed publicly available institutional financial and participation reports at the highest level of athletic competition, National Collegiate Athletic Association (NCAA) Division I. Institutions were grouped by NCAA subdivision status, athletic conference, flagship status, football Bowl Championship Series automatic qualifying status, and several athletic expenses categories. Growth rates between 2005 and 2011 were compared in instructional salaries, tuition rates, athletic coaching salaries, and costs of instruction. Revenue theory of cost and resource dependency theory related these costs within the context of institutional identity to explicate the marketplace of athletics compared to academics in higher education. Descriptive statistics, correlations, ANOVAs, and visual representations were used to analyze the data. The study found the growth rate of total athletic coaching salaries and football coaching salaries far exceeded the corresponding growth rate for instructional salaries at a significant level in all groupings of major college sports.
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See more on www.facebook.com/MonthLongAction
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I consider myself a contributor, change agent and life-long learner. I'm a shipper. And nomad emerging.
This is my public manifesto of who I am, what I seek and offer.
Here you can find out what I did, who I am and what I would like to do with you.
This is the cover slide-deck that I used for 1 hour presentation for 200 young people in Egypt on topic of Effective Communication.
It's not edited for only online preview, so a lot of content is missing, but it is my first slide-deck in this style.
All included photos are from Flickr.com with Creative Commons attribution and share-alike license.
This is also free to share, please if you use the presentation, let me know and attribute :)
This study reviewed publicly available institutional financial and participation reports at the highest level of athletic competition, National Collegiate Athletic Association (NCAA) Division I. Institutions were grouped by NCAA subdivision status, athletic conference, flagship status, football Bowl Championship Series automatic qualifying status, and several athletic expenses categories. Growth rates between 2005 and 2011 were compared in instructional salaries, tuition rates, athletic coaching salaries, and costs of instruction. Revenue theory of cost and resource dependency theory related these costs within the context of institutional identity to explicate the marketplace of athletics compared to academics in higher education. Descriptive statistics, correlations, ANOVAs, and visual representations were used to analyze the data. The study found the growth rate of total athletic coaching salaries and football coaching salaries far exceeded the corresponding growth rate for instructional salaries at a significant level in all groupings of major college sports.
A short advice list as a support for MonthLong of questions initiative. Few tips on how to get the most from the tough questions.
See more on www.facebook.com/MonthLongAction
meet ME - a shipper available, a nomad emergingMarek Lutz
I consider myself a contributor, change agent and life-long learner. I'm a shipper. And nomad emerging.
This is my public manifesto of who I am, what I seek and offer.
Here you can find out what I did, who I am and what I would like to do with you.
This is the cover slide-deck that I used for 1 hour presentation for 200 young people in Egypt on topic of Effective Communication.
It's not edited for only online preview, so a lot of content is missing, but it is my first slide-deck in this style.
All included photos are from Flickr.com with Creative Commons attribution and share-alike license.
This is also free to share, please if you use the presentation, let me know and attribute :)
(SKIP TO SLIDE 113 IF YOU ALREADY KNOW WHAT TWITTER IS.) A presentation I gave at the Nurun Montreal head office in February 2009. The subject covers an idea I had about leveraging the viral potential of Twitter to benefit both its users and third parties looking for some marketing love.
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Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
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A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
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After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Monitoring Java Application Security with JDK Tools and JFR Events
Estudio sobre twitter jun09
1. State of the Twittersphere
June 2009
http://HubSpot.com or @HubSpot
http://Twitter.Grader.com or @Grader
To discuss this report on Twitter use hashtag: #SOTwitter
Compiled by Dan Zarrella @DanZarrella
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2. Overview
Here at HubSpot, we’re big fans of Twitter (you can follow @
HubSpot and @Grader and we built Twitter Grader (http://Twitter.
Grader.com) to help people evaluate and improve their Twitter pres-
ence. With all the data we’ve collected from Twitter Grader (infor-
mation on over 4.5 million users), we thought it was time to update
last year's State of the Twittersphere and share that back with the
community for all of you marketing and Internet geeks (like us).
This time around we think the most interesting points of data we
see center around the “activity” levels of many accounts on Twitter.
For instance:
• 79.79% failed to provide a homepage URL
• 75.86% of users have not entered a bio in their profile
• 68.68% have not specified a location
• 55.50% are not following anyone
• 54.88% have never tweeted
• 52.71% have no followers
In an effort to quantify exactly how many dormant accounts exist,
we labeled users as inactive if they satisfy all of the following condi-
tions:
• Fewer than 10 followers
• Fewer than 10 friends
• Fewer than 10 updates
By this definition, 9.06% of all Twitter users are inactive.
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3. Twitter Growth
In last year’s version of this report, we discovered that Twitter was
growing at an astounding rate of 5-10 thousand new accounts per
day. Clearly that rate has since accelerated and it has reached a
point where it is futile to attempt to generate a flat growth rate num-
ber.
The graph below how the percentage of users of the service who
joined in each month we have data on.
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4. Twitter User Base Statistics
In the last version of the State of the Twittersphere, we reported
that 80% of users had specified a bio in their Twitter profile. This
time around we’ve seen that number (as well as a few other indica-
tors of account activity and completeness) shift dramatically.
• 24.14% of users have a bio in their profile
• 31.32% of users have a location in their profile
• 20.21% of users have a homepage URL in their profile
• 45.12% of users have tweeted at least once
• 47.29% of users have at least one follower
• 44.50% of users are following at least one account
Though we have noticed that those users who are actively using
Twitter do so on a regular basis.
• The average user tweets .97 times per day
• The average user has tweeted 119.34 times in total
• The average user has a following-to-follower ratio of .7738
We have also found that the distribution of following and follower
numbers falls into a pattern very similar to a power-law or “long tail”
curve, as evidenced by the two graphs on the following page.
You’ll notice a spike around 2000 on the following graph, this is due
to the fact that Twitter limits users to only following a maxium of
2000 users untill they have more than 2000 followers.
The y-axis of the following graphs is on a logarithmic scale to allow
for more granularity.
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6. Statistics on Tweets
When we look at the content of tweets that are posted by users we
see that users are frequently using Twitter to interact and communi-
cate with other users rather than just answer the “What are you do-
ing?” question.
• 1.44% of all tweets are retweets
• 37.95% of all tweets contain an “@” symbol (mentions)
• 33.44% of all tweets start with an “@” symbol (replies)
We also see that many users are reaching the 140-character limit in
an attempt to get as much content as possible into every update.
The distribution of posting over days and times-of-day shows us
that business hours during the business week in the US are the
most popular, as seen in the next two graphs.
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8. Geography
Because the location field on Twitter profiles does not contain any
structured data (Twitter does not require people to separate city
from state or province, etc.) it is hard to do any detailed analysis on
this data. However, the list of the top thirty most common phrases
people type into their location section on their bio shows that Twitter
seems to be popular in major English-speaking cities.
Top 20 Locations in Last Report Top 20 Locations in this Report
London London
USA Los Angeles
San Francisco Chicago
New York New York
Chicago San Francisco
Los Angeles Toronto
California Atlanta
Toronto Seattle
Austin, TX Boston
New York, NY Austin
NYC Sydney
San Francisco, CA San Diego
Canada Washington, DC
Texas Melbourne
Atlanta, GA Portland
Washington, DC Houston
UK Vancouver
Los Angeles, CA Dallas
Chicago, IL Brooklyn
new york city Philadelphia
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9. Data Sources
Nearly all of the data in this report comes from http://Twitter.Grader.
com which has information on over 4.5 million Twitter profiles as of
June 2009.
About HubSpot
HubSpot is inbound marketing software that helps your company
get found online, generate more inbound leads and convert a high-
er percentage of them into paying customers. Based in Cambridge,
MA, HubSpot can be found at http://www.HubSpot.com
Find and follow HubSpotters on Twitter: http://www.HubSpot.com/
Twitter
Contributors
Dan Zarrella (inbound marketing manager and author of this re-
port), Dharmesh Shah (co-founder of HubSpot and Twitter Grader
Developer), Mike Volpe (VP of marketing and author of the first ver-
sion of the State of the Twitterphere report).
InboundMarketing.com
InboundMarketing.com is a community for marketers interested in
all forms of inbound marketing. To discuss this report, check out the
forums on http://InboundMarketing.com
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