For years "sentiment" has been a popular metric for showing whether customers like or dislike a company’s products and services. But in the social media era, sentiment really doesn't tell you much -- especially when, on average, only one out of four posts indicates sentiment. This is a real problem when you’re wading through tens or hundreds of thousands of posts, trying to figure out how people feel about your company. You miss a lot of clues about what people are really saying and feeling.
An alternative to sentiment analysis is use of semantic analysis. Semantic analysis uncovers and distills the natural structure around mountains of data – blog posts, social network chatter, tweets and more. In fact, a valuable type of semantic analysis is topic discovery: the summarization of large amounts of text by automatically discovering the topics and themes within. Networked Insights’ new Topic Discovery Engine (TDE) is a semantic analysis system finely tuned to discover topics in social media posts. The valuable information that comes from semantic analysis -- quickly and inexpensively -- can drive product development, new revenue streams and strategies for marketing, advertising and media planning.
This document describes a Twitter analysis project performed in RStudio using R programming. The analysis included collecting tweets containing the hashtag "#Kejriwal", performing sentiment analysis to score the tweets as positive, negative or neutral, and visualizing the results. Text mining was also conducted on the tweets. The sentiment analysis found most tweets had a negative sentiment towards Kejriwal, while text mining showed the most common words in tweets were "Kejriwal", "power", "cut" and "Modi".
Information Propagation Cultures on Sina Weibo and TwitterQi Gao
1) Users on Twitter propagate information faster than those on Sina Weibo, reposting messages within hours rather than days.
2) Messages shared on Twitter tend to contain more hashtags and URLs, indicating users want to profile themselves, while content is prioritized over individualism on Sina Weibo.
3) Chinese microbloggers have a stronger tendency to propagate positive messages, reflecting China's long-term orientation, whereas information shared on Twitter is more balanced between positive and negative.
A Comparative Study of Users' Microblogging Behavior on Sina Weibo and TwitterQi Gao
The document presents findings from a comparative study of microblogging behavior on Sina Weibo and Twitter. Data was collected over 3 months from over 46 million posts from 22 million Sina Weibo users and 24 million Twitter users. The study analyzed differences in user behavior between the two platforms across syntactic, semantic, sentiment and temporal dimensions. Key findings included that Sina Weibo users posted fewer hashtags and URLs, discussed more personal topics, and expressed more positive sentiments compared to more organization-focused and negative Twitter users. Many differences could be explained by cultural dimensions like individualism/collectivism and power distance as described in Hofstede's cultural model.
What Can Big Grocery Learn from Farmers' Markets Using Social Data?Networked Insights
Farmers' markets have grown in popularity significantly in recent decades. Social media analysis reveals that consumers discuss farmers' markets more positively than grocery stores, with a focus on seasonality, freshness, and support for local farms. Grocery stores can learn from this by emphasizing seasonal and locally-sourced products, creating a festive shopping experience, and building strong community connections. Price and availability are less important factors for consumers than experiences focused on fresh, local food and supporting small farms.
Networked Insights Super Bowl XLVIII Brand and Advertising AnalysisNetworked Insights
Networked Insights analyzed over 25 million conversations from social media during Super Bowl XLVIII to provide post-game insights. Their analysis identified the top 10 most popular Super Bowl advertisers based on conversation volume and sentiment, including thematic analysis of top ads. It also ranked the most discussed players, celebrities, and best performing advertisers by key audiences and categories. The methodology used real-time data analysis technologies to segment conversations and understand what messages resonated most with consumers.
1. The Upfronts are annual presentations by TV networks in May to reveal new and returning shows for the fall season and get brands to commit ad spending 4-5 months in advance, though 65% of new shows are cancelled by Christmas.
2. While the Upfronts provide discounts, it is a gamble for brands as shows may not resonate or succeed.
3. Networked Insights used real-time social data and its SocialSense platform to determine which new shows brands should "buy" or "don't buy" and publicized this outside the Upfronts venues to prove marketing decisions can be improved with data and take the gamble out of the Upfronts.
The document discusses how big data and social data are revolutionizing marketing and media. It describes how various technologies and data sources are creating huge amounts of data and new opportunities for companies. Networked Insights leverages social data to help clients make better business decisions by allowing them to pre-inform, stimulate, test, and optimize marketing strategies in real time. The rise of big data is accelerating the marketing lifecycle and allowing all decisions to be data-driven.
Networked Insights analyzed social media conversations during the Super Bowl and Grammys to determine what ads, performances, and celebrities were most discussed. They found that GoDaddy's ad featuring Bar Refaeli was the most talked about Super Bowl commercial. During the Grammys, Jay-Z's joke about The-Dream's hat generated the most tweets per minute, while Rihanna was the most mentioned celebrity overall with over 1.6 million tweets about her. Networked Insights tracks social media conversations to provide marketing analytics companies insights into what is trending and popular.
This document describes a Twitter analysis project performed in RStudio using R programming. The analysis included collecting tweets containing the hashtag "#Kejriwal", performing sentiment analysis to score the tweets as positive, negative or neutral, and visualizing the results. Text mining was also conducted on the tweets. The sentiment analysis found most tweets had a negative sentiment towards Kejriwal, while text mining showed the most common words in tweets were "Kejriwal", "power", "cut" and "Modi".
Information Propagation Cultures on Sina Weibo and TwitterQi Gao
1) Users on Twitter propagate information faster than those on Sina Weibo, reposting messages within hours rather than days.
2) Messages shared on Twitter tend to contain more hashtags and URLs, indicating users want to profile themselves, while content is prioritized over individualism on Sina Weibo.
3) Chinese microbloggers have a stronger tendency to propagate positive messages, reflecting China's long-term orientation, whereas information shared on Twitter is more balanced between positive and negative.
A Comparative Study of Users' Microblogging Behavior on Sina Weibo and TwitterQi Gao
The document presents findings from a comparative study of microblogging behavior on Sina Weibo and Twitter. Data was collected over 3 months from over 46 million posts from 22 million Sina Weibo users and 24 million Twitter users. The study analyzed differences in user behavior between the two platforms across syntactic, semantic, sentiment and temporal dimensions. Key findings included that Sina Weibo users posted fewer hashtags and URLs, discussed more personal topics, and expressed more positive sentiments compared to more organization-focused and negative Twitter users. Many differences could be explained by cultural dimensions like individualism/collectivism and power distance as described in Hofstede's cultural model.
What Can Big Grocery Learn from Farmers' Markets Using Social Data?Networked Insights
Farmers' markets have grown in popularity significantly in recent decades. Social media analysis reveals that consumers discuss farmers' markets more positively than grocery stores, with a focus on seasonality, freshness, and support for local farms. Grocery stores can learn from this by emphasizing seasonal and locally-sourced products, creating a festive shopping experience, and building strong community connections. Price and availability are less important factors for consumers than experiences focused on fresh, local food and supporting small farms.
Networked Insights Super Bowl XLVIII Brand and Advertising AnalysisNetworked Insights
Networked Insights analyzed over 25 million conversations from social media during Super Bowl XLVIII to provide post-game insights. Their analysis identified the top 10 most popular Super Bowl advertisers based on conversation volume and sentiment, including thematic analysis of top ads. It also ranked the most discussed players, celebrities, and best performing advertisers by key audiences and categories. The methodology used real-time data analysis technologies to segment conversations and understand what messages resonated most with consumers.
1. The Upfronts are annual presentations by TV networks in May to reveal new and returning shows for the fall season and get brands to commit ad spending 4-5 months in advance, though 65% of new shows are cancelled by Christmas.
2. While the Upfronts provide discounts, it is a gamble for brands as shows may not resonate or succeed.
3. Networked Insights used real-time social data and its SocialSense platform to determine which new shows brands should "buy" or "don't buy" and publicized this outside the Upfronts venues to prove marketing decisions can be improved with data and take the gamble out of the Upfronts.
The document discusses how big data and social data are revolutionizing marketing and media. It describes how various technologies and data sources are creating huge amounts of data and new opportunities for companies. Networked Insights leverages social data to help clients make better business decisions by allowing them to pre-inform, stimulate, test, and optimize marketing strategies in real time. The rise of big data is accelerating the marketing lifecycle and allowing all decisions to be data-driven.
Networked Insights analyzed social media conversations during the Super Bowl and Grammys to determine what ads, performances, and celebrities were most discussed. They found that GoDaddy's ad featuring Bar Refaeli was the most talked about Super Bowl commercial. During the Grammys, Jay-Z's joke about The-Dream's hat generated the most tweets per minute, while Rihanna was the most mentioned celebrity overall with over 1.6 million tweets about her. Networked Insights tracks social media conversations to provide marketing analytics companies insights into what is trending and popular.
Only 16% of discussions around the film Argo from January 10th to February 14th, 2013 centered on the Academy snubbing Ben Affleck for Best Director. Similarly, only 5% of conversations about the film Zero Dark Thirty during that same time period focused on its polarizing torture scenes.
This document analyzes social media conversations around seven holiday films from 2012. It finds that Les Miserables had significantly more online discussion than other films, as measured by its social index score of 236. The social index combines conversation volume, sentiment, and acceleration to compare how topics perform relative to their peers. While box office is unpredictable, Les Miserables was winning the conversation race on social media. The document also examines key moments that drove discussion for each film and identifies audience demographics involved in online conversations.
Insights from super bowl xlvii 2013 post game analysis (brands + celebs) 20...Networked Insights
This document provides a summary of social media analysis conducted on conversations during Super Bowl XLVII. Over 24 million conversations across Twitter, Facebook, blogs and forums were analyzed. The top discussed topics were Beyonce's halftime show at 32%, the Ravens at 21%, and the 49ers at 17%. Analysis also looked at the top 10 advertised brands based on conversation volume and sentiment, and provided a deeper analysis of the ads from Taco Bell, Tide, and GoDaddy that resonated most with viewers.
The document outlines 8 trends in marketing: 1) Brands will produce more of their own content instead of relying on agencies. 2) Publishers will gain more control over content from media agencies. 3) Brands will form syndicates to expand their networks. 4) Digital technology will continue to influence television. 5) Sequencing different marketing tactics will become more important than integrating them. 6) Marketers will focus on the minimal effective amount of spending. 7) Media planning will shift to a performance-based model like media buying. 8) Consumer interactions and user-generated content will indicate future trends.
This document discusses how to identify influential social media users, or "influencers", to help market products and brands. It defines what makes someone an influencer based on their reach, resonance, and relevance on social platforms. It also provides examples of how analyzing influencers helped a consumer tech company influence other influencers, a CPG company amplify a celebrity's message, and a mobile tech company find the right celebrity ambassador. The key is balancing an influencer's social impact with the cost of their endorsement.
Making marketing decisions at the speed of your consumerNetworked Insights
Learn how real-time data-driven marketing is changing the way innovative companies do business, and how Networked Insights is the secret sauce you're missing in your marketing mix.
The document provides a summary of the most anticipated new fall TV shows for 2012 according to social media analysis between May 1 and September 13, 2012. It lists the shows by network and provides key details about each show such as the premise, notable cast members, and emerging themes in online conversations. The shows receiving the most anticipation were The New Normal on NBC, Revolution on NBC, and The Following on Fox.
CMOs: How to Spend the Minimal Effective Amount on MediaNetworked Insights
Learn how this new form of “marketing intelligence” can dramatically reduce wasted spending and contribute even more effectively to earnings per share.
Anticipation is building for Sunday’s Super Bowl, and we know the excitement isn’t just about the game. Brands are making huge bets that they’re ads will capture the interest, and ultimately the business, of the millions who’ll be watching.Even if your company isn’t one of those laying out millions for game-time airtime, there are still ways you can get in on the action. Networked Insights’ Media Optimization Guide, Super Bowl XLVI Edition will show you how to use social data to make every ad perform like a Super Bowl ad using our Audience Sync, Content Sync and Media Sync tools.
The guide discusses how you can use real-time social data to understand your audiences and deliver them relevant content. It reveals how you can reach NFL fans without an NFL budget, and how you can overcome a media lockout. The guide also has tips on leveraging social data to understand a TV show’s audience before it airs, and it takes a look at how you can improve your TV marketing with real-time audience intelligence. Want more? Let’s just say that the social buzz around Madonna’s halftime performance is going to be quite a story unto itself.
Stage-Gate success: How the social web drives product developmentNetworked Insights
Social data is becoming increasingly important in the new product development processes of many companies. In particular, manufacturers are tapping into social conversations as they explore new product ideas in order to learn what consumers are interested in and talking about. Later, when launch is imminent, social channels are becoming a key factor in setting media and advertising strategies.
For most people, Black Friday kicks off the holiday shopping season. It’s a time of year to relish terrific savings and wonderful retail experiences. Others find all the activity too frenzied to participate, saving their dollars and time for Cyber Monday. No matter where you stand on the spectrum of holiday consumerism, it’s undeniably the most important time of year for most brands and retailers.
Download the 2011 Retail Brands Report and see how consumers speak about the five largest retail brands in social media and discover how and why brands relate to their customers. Networked Insights’s analysts examined real-time consumer data to reveal trending topics and brand conversations, as well as insights on consumer behavior/preference, all segmented by five different consumer types.
Is search always the right solution? There are many things you can do with a hammer, but it’s not so great if you need to turn a screw.
Text Classification is an alternative to search that may be more appropriate for social media data analysis. Text classification is the task of assigning predefined categories to free-text documents. It can provide conceptual views of document collections and has important applications in the real world. Using text classification as the foundation for analysis – i.e., teaching a machine to categorize posts the way humans do – can dramatically improve your ability to gather the right data and, ultimately, increase the chances that you’ll uncover what you need to know.
Brands that sponsored Kim Kardashian's wedding hoped to earn publicity from social media conversations. Vera Wang received the highest return on its investment of $60,000 in wedding dresses, doubling to $120,000 in brand value. Perrier-Jouet came in second with a 48% return on its $500,000 investment. People Magazine spent $2.5 million on exclusive photos but only earned $1,115,000 in brand value due to relatively low increased conversations, resulting in a 45% loss.
1) Corporate Social Network Analytics
NOTE: both internal and external social networks (assuming there is an internal network - an example could be SharePoint)
(per week, per month, per quarter, per year)
- Total # of Posts
- Sentiment of Posts
- Pie Chart of Contributing Sites - SharePoint, Facebook, Twitter, LinkedIn
- Content trends (tag cloud)
- Total time spent
- Total number of pages viewed
- Top contributors (leader board)
2) Profile of someone on the leader board
(per week, per month, per quarter, per year)
- Total # of Posts
- Pie Chart of Contributing Sites - SharePoint, Facebook, Twitter, LinkedIn
- Content trends (tag cloud)
- Total time spent
- Total number of pages viewed
- Dollar amount of his connections (I have the algorithm for this)
The Season 4 premiere of True Blood in June was the hit that series producers had hoped for, matching the show’s highest ratings ever. Such strong numbers for the season opener of the HBO series weren’t a surprise though to anyone tracking the social media conversation leading up to, during and right after the episode. Fang fans flocked to blogs, Twitter, Facebook, HBO.com and other sites to profess their love for the show, speculate where Sookie and Eric’s relationship is heading, and revisit key events in past episodes. Networked Insights’ Social Intelligence Report: True Blood describes our analysis of the social conversation surrounding the hit season-opening episode “She’s Not There.”
The document summarizes why sentiment analysis often fails and presents semantic analysis as a better alternative. It argues that sentiment analysis has a narrow view of meaning, ignores most data, and leaves results up to chance due to low statistical confidence. In contrast, semantic analysis analyzes all data, understands the entire conversation, and determines results based on data rather than chance. The document recommends asking providers of sentiment analysis about inter-reader agreement, number of readers per post, and type of posts analyzed, to assess the reliability of sentiment results.
Social media optimizes your ad dollars!
When networks publish upfronts in the spring, advertisers are waiting with baited breathe to see gross rating points, target rating points, total households of the most popular programs. But that's the problem, isn't it? They're all looking at the same information and vying for the same advertising action. Want to get the jump on your competitors when the new line-ups are aired this fall?
7 Ways to Inform your Media Planning using Social DataNetworked Insights
Consumers are talking about brands more than ever before online. Social Media captures these conversations in various forms and if tapped right can uncover a vast array of information that can impact your media investments. Applying this knowledge to optimize your ad spend can generate efficiencies of more than 10 percent! Join Adweek and Networked Insights for a free webinar and dig deeper into Social Media data and get past GRPs & TRPs to uncover what consumers are talking about and where - just in time for the upfronts.
In this webinar you will learn:
* Value gained exploiting shows undervalued by Nielsen.
* Hyper-segmentation approaches that go beyond "Adults 18 to 49."
* How social can point the way to premium audiences at non-premium prices.
* How to coordinate paid, earned, and owned assets to generate a "social lift" and make your spend go farther.
How to Infuse Your Media Planning with Social Data - by Forrester & Networked...Networked Insights
Consumers are talking about brands more than ever before online. Social Media captures these conversations in various forms and if tapped right can uncover a vast array of information that can impact your media investments. Applying this knowledge to optimize your ad spend can generate efficiencies of more than 10 percent! Join Adweek and Networked Insights for a free webinar and dig deeper into Social Media data and get past GRPs & TRPs to uncover what consumers are talking about and where - just in time for the upfronts.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Only 16% of discussions around the film Argo from January 10th to February 14th, 2013 centered on the Academy snubbing Ben Affleck for Best Director. Similarly, only 5% of conversations about the film Zero Dark Thirty during that same time period focused on its polarizing torture scenes.
This document analyzes social media conversations around seven holiday films from 2012. It finds that Les Miserables had significantly more online discussion than other films, as measured by its social index score of 236. The social index combines conversation volume, sentiment, and acceleration to compare how topics perform relative to their peers. While box office is unpredictable, Les Miserables was winning the conversation race on social media. The document also examines key moments that drove discussion for each film and identifies audience demographics involved in online conversations.
Insights from super bowl xlvii 2013 post game analysis (brands + celebs) 20...Networked Insights
This document provides a summary of social media analysis conducted on conversations during Super Bowl XLVII. Over 24 million conversations across Twitter, Facebook, blogs and forums were analyzed. The top discussed topics were Beyonce's halftime show at 32%, the Ravens at 21%, and the 49ers at 17%. Analysis also looked at the top 10 advertised brands based on conversation volume and sentiment, and provided a deeper analysis of the ads from Taco Bell, Tide, and GoDaddy that resonated most with viewers.
The document outlines 8 trends in marketing: 1) Brands will produce more of their own content instead of relying on agencies. 2) Publishers will gain more control over content from media agencies. 3) Brands will form syndicates to expand their networks. 4) Digital technology will continue to influence television. 5) Sequencing different marketing tactics will become more important than integrating them. 6) Marketers will focus on the minimal effective amount of spending. 7) Media planning will shift to a performance-based model like media buying. 8) Consumer interactions and user-generated content will indicate future trends.
This document discusses how to identify influential social media users, or "influencers", to help market products and brands. It defines what makes someone an influencer based on their reach, resonance, and relevance on social platforms. It also provides examples of how analyzing influencers helped a consumer tech company influence other influencers, a CPG company amplify a celebrity's message, and a mobile tech company find the right celebrity ambassador. The key is balancing an influencer's social impact with the cost of their endorsement.
Making marketing decisions at the speed of your consumerNetworked Insights
Learn how real-time data-driven marketing is changing the way innovative companies do business, and how Networked Insights is the secret sauce you're missing in your marketing mix.
The document provides a summary of the most anticipated new fall TV shows for 2012 according to social media analysis between May 1 and September 13, 2012. It lists the shows by network and provides key details about each show such as the premise, notable cast members, and emerging themes in online conversations. The shows receiving the most anticipation were The New Normal on NBC, Revolution on NBC, and The Following on Fox.
CMOs: How to Spend the Minimal Effective Amount on MediaNetworked Insights
Learn how this new form of “marketing intelligence” can dramatically reduce wasted spending and contribute even more effectively to earnings per share.
Anticipation is building for Sunday’s Super Bowl, and we know the excitement isn’t just about the game. Brands are making huge bets that they’re ads will capture the interest, and ultimately the business, of the millions who’ll be watching.Even if your company isn’t one of those laying out millions for game-time airtime, there are still ways you can get in on the action. Networked Insights’ Media Optimization Guide, Super Bowl XLVI Edition will show you how to use social data to make every ad perform like a Super Bowl ad using our Audience Sync, Content Sync and Media Sync tools.
The guide discusses how you can use real-time social data to understand your audiences and deliver them relevant content. It reveals how you can reach NFL fans without an NFL budget, and how you can overcome a media lockout. The guide also has tips on leveraging social data to understand a TV show’s audience before it airs, and it takes a look at how you can improve your TV marketing with real-time audience intelligence. Want more? Let’s just say that the social buzz around Madonna’s halftime performance is going to be quite a story unto itself.
Stage-Gate success: How the social web drives product developmentNetworked Insights
Social data is becoming increasingly important in the new product development processes of many companies. In particular, manufacturers are tapping into social conversations as they explore new product ideas in order to learn what consumers are interested in and talking about. Later, when launch is imminent, social channels are becoming a key factor in setting media and advertising strategies.
For most people, Black Friday kicks off the holiday shopping season. It’s a time of year to relish terrific savings and wonderful retail experiences. Others find all the activity too frenzied to participate, saving their dollars and time for Cyber Monday. No matter where you stand on the spectrum of holiday consumerism, it’s undeniably the most important time of year for most brands and retailers.
Download the 2011 Retail Brands Report and see how consumers speak about the five largest retail brands in social media and discover how and why brands relate to their customers. Networked Insights’s analysts examined real-time consumer data to reveal trending topics and brand conversations, as well as insights on consumer behavior/preference, all segmented by five different consumer types.
Is search always the right solution? There are many things you can do with a hammer, but it’s not so great if you need to turn a screw.
Text Classification is an alternative to search that may be more appropriate for social media data analysis. Text classification is the task of assigning predefined categories to free-text documents. It can provide conceptual views of document collections and has important applications in the real world. Using text classification as the foundation for analysis – i.e., teaching a machine to categorize posts the way humans do – can dramatically improve your ability to gather the right data and, ultimately, increase the chances that you’ll uncover what you need to know.
Brands that sponsored Kim Kardashian's wedding hoped to earn publicity from social media conversations. Vera Wang received the highest return on its investment of $60,000 in wedding dresses, doubling to $120,000 in brand value. Perrier-Jouet came in second with a 48% return on its $500,000 investment. People Magazine spent $2.5 million on exclusive photos but only earned $1,115,000 in brand value due to relatively low increased conversations, resulting in a 45% loss.
1) Corporate Social Network Analytics
NOTE: both internal and external social networks (assuming there is an internal network - an example could be SharePoint)
(per week, per month, per quarter, per year)
- Total # of Posts
- Sentiment of Posts
- Pie Chart of Contributing Sites - SharePoint, Facebook, Twitter, LinkedIn
- Content trends (tag cloud)
- Total time spent
- Total number of pages viewed
- Top contributors (leader board)
2) Profile of someone on the leader board
(per week, per month, per quarter, per year)
- Total # of Posts
- Pie Chart of Contributing Sites - SharePoint, Facebook, Twitter, LinkedIn
- Content trends (tag cloud)
- Total time spent
- Total number of pages viewed
- Dollar amount of his connections (I have the algorithm for this)
The Season 4 premiere of True Blood in June was the hit that series producers had hoped for, matching the show’s highest ratings ever. Such strong numbers for the season opener of the HBO series weren’t a surprise though to anyone tracking the social media conversation leading up to, during and right after the episode. Fang fans flocked to blogs, Twitter, Facebook, HBO.com and other sites to profess their love for the show, speculate where Sookie and Eric’s relationship is heading, and revisit key events in past episodes. Networked Insights’ Social Intelligence Report: True Blood describes our analysis of the social conversation surrounding the hit season-opening episode “She’s Not There.”
The document summarizes why sentiment analysis often fails and presents semantic analysis as a better alternative. It argues that sentiment analysis has a narrow view of meaning, ignores most data, and leaves results up to chance due to low statistical confidence. In contrast, semantic analysis analyzes all data, understands the entire conversation, and determines results based on data rather than chance. The document recommends asking providers of sentiment analysis about inter-reader agreement, number of readers per post, and type of posts analyzed, to assess the reliability of sentiment results.
Social media optimizes your ad dollars!
When networks publish upfronts in the spring, advertisers are waiting with baited breathe to see gross rating points, target rating points, total households of the most popular programs. But that's the problem, isn't it? They're all looking at the same information and vying for the same advertising action. Want to get the jump on your competitors when the new line-ups are aired this fall?
7 Ways to Inform your Media Planning using Social DataNetworked Insights
Consumers are talking about brands more than ever before online. Social Media captures these conversations in various forms and if tapped right can uncover a vast array of information that can impact your media investments. Applying this knowledge to optimize your ad spend can generate efficiencies of more than 10 percent! Join Adweek and Networked Insights for a free webinar and dig deeper into Social Media data and get past GRPs & TRPs to uncover what consumers are talking about and where - just in time for the upfronts.
In this webinar you will learn:
* Value gained exploiting shows undervalued by Nielsen.
* Hyper-segmentation approaches that go beyond "Adults 18 to 49."
* How social can point the way to premium audiences at non-premium prices.
* How to coordinate paid, earned, and owned assets to generate a "social lift" and make your spend go farther.
How to Infuse Your Media Planning with Social Data - by Forrester & Networked...Networked Insights
Consumers are talking about brands more than ever before online. Social Media captures these conversations in various forms and if tapped right can uncover a vast array of information that can impact your media investments. Applying this knowledge to optimize your ad spend can generate efficiencies of more than 10 percent! Join Adweek and Networked Insights for a free webinar and dig deeper into Social Media data and get past GRPs & TRPs to uncover what consumers are talking about and where - just in time for the upfronts.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen