Ordinary individuals on Twitter have more influence than previously thought. While a small number of highly influential "opinion leaders" do exist, the average individual influences just one other person. However, because there are so many ordinary influencers, targeting them collectively could be more cost-effective than targeting the rare highly influential individuals alone. The study analyzed billions of tweets and diffusion "cascades" to predict influence, finding that past influence and number of followers were most predictive, though influence was still difficult to predict for individuals. Content attributes like interestingness and positive sentiment also correlated with larger cascades.
Tech backpack Brief for Causes, Philanthropy and CharitiesTech Backpack
Social media publishing tools for digital storytellers, to help you save time to research, write and distribute your content and stories with news organizations.
Tech backpack Brief for Causes, Philanthropy and CharitiesTech Backpack
Social media publishing tools for digital storytellers, to help you save time to research, write and distribute your content and stories with news organizations.
Email automation is pretty awesome. How awesome? Well, setting up the right workflows can help increase the efficiency of your marketing and create a more impactful inbox experience for your subscribers. And a better experience builds trust with your brand that can lead to some seriously impressive conversions, sales, customer engagement and more!
5 attention zones in the age of the internet Emily Hean
PEW data shows that we consume content in 5 distinct ways Streams, Stacks, Snacks, Socials and Signals. Info from Lee Rainie and the PEW internet project. Within the last 15 years how we find and consumer information has changed drastically because of the pervasive reach of broadband internet, mobile connectivity and social networking.
This presentation focuses on the importance of identifying influencers within a social network. This is a synopsis of an SMU graduate paper (Word doc) in fulfillment of my Masters in Advertising - New Media.
How do we measure the total value brought in by a customer to a firm through social media? This presentation follows our research to create a metric called the total customer value and identify what drives customers to follow, influence and make purchases through Twitter
{White Paper} Measuring Global Attention | AppinionsAppinions
There are many associations that come to mind when people hear the word, “influence.” Power. Prestige. Prominence. However, what it boils down to is the ability to capture peoples’ attention. When an individual expresses an opinion in traditional or online media, which then travels beyond its original source, that individual has managed to capture attention. How far the opinion travels, and over what networks and media, help define how much influence an individual is generating based on that opinion.
In this white paper, Appinions’ Chief Technology Officer, David Pierce and data scientist, Stewart Siu, shed light on our approach to influence from a technical point of view.
Understand and Unleash the Power of Word of Mouth MarketingRipple6, Inc.
Augie Ray is a Senior Analyst from Forrester Research, an independent research company that provides pragmatic and forward-thinking advice to global leaders in business and technology.
In this information-packed session, you will learn how to develop successful programs that draw in, engage, and leverage the power of social influencers to create brand advocates. Topics will include:
• Creating brand advocates
• Measuring peer influence
• Leveraging brand advocates across the digital landscape
• Driving results from a strong social strategy
You will also learn how the Ripple6 Social Hub can help you scale your social efforts and get the most out of your social strategy:
• Create a critical mass of users and conversations
• Distribute your messages, manage and engage with your audience wherever they are across the web, social networks, your brand site, mobile and more
• Easily extend into Facebook and Twitter from a single point of entry
• Turn your brand web site into a thriving conversational marketing vehicle
2013 Johns Hopkins School of Public Health LectureDouglas Joubert
Course lecture for the Johns Hopkins School of Public Health lecture: A New View: Improving Public Health through Innovative Social and Behavioral Tools and Approaches.
The Future of Influence, Northern Voice 2009nate_elliott
Presentation on The Future of Influence by Forrester Principal Analyst Nate Elliott. Delivered at Northern Voice 2009 in Vancouver BC, February 21, 2009.
These are the slides of a keynote I gave at Emerce Eday on 25 October 2012 in Rotterdam.
The short description of my talk was as follows: With the ongoing rise of third party applications like Klout, tools for measuring Twitter influence are important to understand. This presentation takes a look at the different ways in which influence measures have been developed for Twitter. In particular it will use the case study of the UK riots of 2011 for which a database of 2.6 million tweets was collected in collaboration with Twitter and The Guardian newspaper. By examining the top 1000 most tweeted accounts, it will give further insight in how influence worked during this crisis event, specifically highlighting the emergence of the ‘ordinary influential’ during 2011 as well as how large organisations have incorporated social media practices.
Originally presented by Monique Ramsey at Congress on Aesthetic Vaginal Surgery (CAVS) and the National Society of Cosmetic Physicians (NSOCP) Annual Meeting held at the Cosmopolitan Resort and Casino, Las Vegas, Nevada, September 19-22, 2013.
Social Media Influencers of 2010. A recently launched social media influencers report y Fresh Networks tests how effective nine of the leading social media monitoring tools are at identifying influencers.
Email automation is pretty awesome. How awesome? Well, setting up the right workflows can help increase the efficiency of your marketing and create a more impactful inbox experience for your subscribers. And a better experience builds trust with your brand that can lead to some seriously impressive conversions, sales, customer engagement and more!
5 attention zones in the age of the internet Emily Hean
PEW data shows that we consume content in 5 distinct ways Streams, Stacks, Snacks, Socials and Signals. Info from Lee Rainie and the PEW internet project. Within the last 15 years how we find and consumer information has changed drastically because of the pervasive reach of broadband internet, mobile connectivity and social networking.
This presentation focuses on the importance of identifying influencers within a social network. This is a synopsis of an SMU graduate paper (Word doc) in fulfillment of my Masters in Advertising - New Media.
How do we measure the total value brought in by a customer to a firm through social media? This presentation follows our research to create a metric called the total customer value and identify what drives customers to follow, influence and make purchases through Twitter
{White Paper} Measuring Global Attention | AppinionsAppinions
There are many associations that come to mind when people hear the word, “influence.” Power. Prestige. Prominence. However, what it boils down to is the ability to capture peoples’ attention. When an individual expresses an opinion in traditional or online media, which then travels beyond its original source, that individual has managed to capture attention. How far the opinion travels, and over what networks and media, help define how much influence an individual is generating based on that opinion.
In this white paper, Appinions’ Chief Technology Officer, David Pierce and data scientist, Stewart Siu, shed light on our approach to influence from a technical point of view.
Understand and Unleash the Power of Word of Mouth MarketingRipple6, Inc.
Augie Ray is a Senior Analyst from Forrester Research, an independent research company that provides pragmatic and forward-thinking advice to global leaders in business and technology.
In this information-packed session, you will learn how to develop successful programs that draw in, engage, and leverage the power of social influencers to create brand advocates. Topics will include:
• Creating brand advocates
• Measuring peer influence
• Leveraging brand advocates across the digital landscape
• Driving results from a strong social strategy
You will also learn how the Ripple6 Social Hub can help you scale your social efforts and get the most out of your social strategy:
• Create a critical mass of users and conversations
• Distribute your messages, manage and engage with your audience wherever they are across the web, social networks, your brand site, mobile and more
• Easily extend into Facebook and Twitter from a single point of entry
• Turn your brand web site into a thriving conversational marketing vehicle
2013 Johns Hopkins School of Public Health LectureDouglas Joubert
Course lecture for the Johns Hopkins School of Public Health lecture: A New View: Improving Public Health through Innovative Social and Behavioral Tools and Approaches.
The Future of Influence, Northern Voice 2009nate_elliott
Presentation on The Future of Influence by Forrester Principal Analyst Nate Elliott. Delivered at Northern Voice 2009 in Vancouver BC, February 21, 2009.
These are the slides of a keynote I gave at Emerce Eday on 25 October 2012 in Rotterdam.
The short description of my talk was as follows: With the ongoing rise of third party applications like Klout, tools for measuring Twitter influence are important to understand. This presentation takes a look at the different ways in which influence measures have been developed for Twitter. In particular it will use the case study of the UK riots of 2011 for which a database of 2.6 million tweets was collected in collaboration with Twitter and The Guardian newspaper. By examining the top 1000 most tweeted accounts, it will give further insight in how influence worked during this crisis event, specifically highlighting the emergence of the ‘ordinary influential’ during 2011 as well as how large organisations have incorporated social media practices.
Originally presented by Monique Ramsey at Congress on Aesthetic Vaginal Surgery (CAVS) and the National Society of Cosmetic Physicians (NSOCP) Annual Meeting held at the Cosmopolitan Resort and Casino, Las Vegas, Nevada, September 19-22, 2013.
Social Media Influencers of 2010. A recently launched social media influencers report y Fresh Networks tests how effective nine of the leading social media monitoring tools are at identifying influencers.
Digging for data: opportunities and challenges in an open research landscape_...Platforma Otwartej Nauki
“Open Research Data: Implications for Science and Society”, Warsaw, Poland, May 28–29, 2015, conference organized by the Open Science Platform — an initiative of the Interdisciplinary Centre for Mathematical and Computational Modelling at the University of Warsaw. pon.edu.pl @OpenSciPlatform #ORD2015
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
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.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
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.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 3
Ordinary Influencers on Twitter
1. “Ordinary Influencers” on Twitter Eytan Bakshy1 Jake M. Hofman2 Winter A. Mason2 Duncan J. Watts2 1 University of Michigan 2 Yahoo! Research
2. “Influentials” and Word-Of-Mouth Marketing Research in 1950’s emphasized importance of personal influence Trusted ties more important than media influence in determining individual opinions Also found that not all people are equally influential A minority of “opinion leaders” or “influentials” are responsible for influencing everyone else Call this the “influentials hypothesis” “One in ten Americans tells the other nine how to vote, where to eat, and what to buy.” (Keller and Berry, 2003)
3. Twitter Well Suited For Identifying Influencers Well-defined, fully-observable network of individuals who explicitly opt-in to follow each other Twitter users are expressly motivated to be heard Includes many types of potential influencers Formal organizations (media, government, brands) Celebrities (Ashton, Shaq, Oprah) Public and Semi-Public Figures (bloggers, authors, journalists, public intellectuals) Private Individuals Many “tweets” include unique URLs which Can originate from multiple sources (“seeds”) Can be tracked over multiple hops (“cascades”)
4. Computing Influence on Twitter An individual “seed” user tweets a URL (here we consider only bit.ly) For every follower who subsequently posts same URL (whether explicit “retweet” or not), seed accrues 1 pt Repeat for followers-of-followers, etc. to obtain total influence score for that “cascade” Where multiple predecessors exist, credit first poster Can also split credit or credit last poster (no big changes) Average individual influence score over all cascades Highly conservative measure of influence, as it requires not only seeing but acting on a tweet Click-through would be good, but not available to us
5. Data Crawl of Twitter follower graph: 56M unique twitter users 1.7B edges Twitter “firehose” tweet stream: 15 Sept 2009 – 15 Nov 2009 ~1B tweets Focus on bit.ly URLs 87M tweets 1.6M “seed” users 74M diffusion events
6. Take-home points In general, nothing goes viral Attributes of the user & content are related to larger cascades Number of followers, size of average past cascade Interestingness & positive feelings But these are not sufficient conditions for large cascades Depending on the cost function of targeting users, casting a wide net may be more efficient than targeting “influencers”
7. Cascades on Twitter 1.6M distinct “seeds” Each seed posts average of 46.3 bit.ly URL’s 74M cascades total Mean cascade size 1.14 Median cascade size 1 Mean influence score 0.14
8. Most Tweets Don’t Spread Almost all cascades are small and shallow A tiny fraction are large and propagate up to 8 hops Even large cascades only reach thousands
9. Predicting Influence Objective is to predict influence score for future cascades as function of # Followers, # Friends, # Reciprocated Ties # Tweets, Time of joining Past influence score Fit data using regression tree Recursively partitions feature space Piecewise constant function fit to mean of training data in each partition Nonlinear, non-parametric Better calibrated than ordinary linear regression Use five-fold cross-validation For each fold, estimate model on training data, then evaluate on test data Every user gets included in one test set
10. Results Only two features matter Past local influence # Followers Surprisingly, neither # tweets nor # following matter
11. Results Model is well calibrated average predicted close to average actual within partitions But fit is poor (R2 = 0.34) Reflects individual scatter
12. Who are the Influencers? Circles represent individual seeds (sized by influence)
18. The Role of Content Surprisingly, content does not matter relative to user features Even with content, fit is poor (R2 = 0.31) Much smaller subset
19. Necessary but not sufficient Seeds of large cascades share certain features (e.g., high degree, past influence) However, many small cascades share those features, making “success” hard to predict at individual level Common problem for rare events School shootings, Plane crashes, etc. Tempting to infer causality from “events,” but causality disappears once non-events accounted for Lesson for marketers: Individual level predictions are unreliable, even given “perfect” information Fortunately, can target many seeds, thereby harnessing average effects
20. Cost-effectiveness of targeting strategies On average, some types of influencers are more influential than others Many of them are highly visible celebrities, etc. with millions of followers But these individuals may also be very expensive Assume the following cost function ci = ca +fi*cf, where ca = acquisition cost; cf = per-follower cost Also ca = a*cf, where a expresses cost of acquiring individual users relative to sponsoring individual tweets Should you target: A small # of highly influential seeds? A large # of ordinary seeds with few followers? Somewhere in between?
21. “Ordinary Influencers” Dominate Assume cf = $0.01 Equivalent to paying $10K per tweet for user with 1M followers When ca = $1,000, (a = 100,000) highly influential users are most cost effective When ca ≤ $100, (a = 10,000), most efficient choice are low-influence users Influence per Follower
22. Broader Implications Twitter is a special case So need to apply same method to other cases Nevertheless, result that large cascades are rare is probably general “Social epidemics” are extremely rare Difficult to predict them or how they will start “Big seed” approach is more reliable “Ordinary Influencers” seem unexciting Only influence one other person on average But average influence is close to zero (0.28); so they’re still more influential than average Combined with mass media could be very powerful.