- When it’s about spreading information, social media platforms are the biggest medium.
- As search and social giants are providing special measures, this article takes a look at what Twitter has done to support people around the globe during these testing times.
- Twitter condemned any spread of misleading information on its platform.
- Twitter further donated a million dollars to support journalism during the pandemic.
- More details on all these and a list of reliable Twitter accounts you can follow for accurate information.
The Coronavirus pandemic has created some unusual times and as we know unusual times call for extraordinary measures. As search and social giants are providing special measures, this article takes a look at what Twitter has done to support people around the globe during these testing times.
The role of social media during the pandemic
Social media platforms account to entertain almost 4.6 billion people from all around the world. The leading platforms Facebook, Instagram, Twitter, and YouTube are among the top contributor to creating a well-connected platform for active users. News and updates spread within second on these platforms reaching to millions, fastest than the one broadcasted through television channels. So, when it’s about spreading information, social media platforms are the biggest medium.
At present, every single platform is making their efforts to creating the safest channel to spread information and to soothe the people down while guiding them about the havocs of the pandemic and ways through which they can save themselves. In this struggle, let’s discuss the role of Twitter, one of the most crowded social media platforms.
How Twitter is taking care of its users
Twitter is a free platform to socialize. With the use of hashtags and a seamless interface, users are connected with each other despite the region they belong to. During the first three months of 2020, active users on Twitter maximized which reflects its authenticity and positioning among the active social media users. In fact, Twitter ad engagement is up 23%.
With the onset of the pandemic, social media platforms have to face a number of accusations. One of the most important accusations was the spread of false information.
Banned misinformation from the platform
Twitter condemned any spread of misleading information on its platform. As the platform entertains millions of users, the spread of misinformation was creating panic among the users and misleading them regarding the seriousness of the Pandemic. At last, the microblogging platform got updated and any information that was verified as false or manipulative gets instantly deleted. Much like Facebook, the platform began to promote information by verifying it from credible sources. Whether it’s about the global healthcare spending statistic or the count of infected patients around the world, the accurate numbers began to spread.
Source: Twitter Safety Status
Among the prominent aspects been observed to banning the content involved untrue information about the affected ones, reasons that triggered the virus claims about specific religious groups or communities getting prone to the disease, racism, and discrimination. Anything related to these aspects gets deleted and banned in an instant.
Apart from this, Twitter authorities also informed about efforts being taken to automate the removal of abusive and manipulated posts. With the help of machine learning, the platform gets scrutinize and any content that can cause harm to an individual gets restricted to share or post. In the following words, the authorities made their claim about the updates, “As we’ve said on many occasions, our approach to protecting the public conversation is never static. That’s particularly relevant in these unprecedented times. We intend to review our thinking daily and will ensure we’re sharing updates here on any new clarifications to our rules or major changes to how we’re enforcing them,”
Twitter Donates a million dollars to support journalism during the pandemic
Just when the news about banning misleading information on Twitter was making the headlines, Twitter released a new update about its contribution. The platform is donating a million dollars to two organizations The International Women’s Media Foundation and the Committee to Protect Journalists to report authentic news about the COVID-19 pandemic. It proves to be a great step in keeping the world safe from the pandemic any guiding more and more people about ways to prevent getting affected. The journalist will shed light on all the stories that can prove to be helpful in fighting the outbreak.
As journalists are playing a major role in getting into the government and healthcare sectors and scooping out authentic and rich information about the Coronavirus, it’s imperative to appreciate and help them. Journalists all around the world are among the front line warriors to defeat the pandemic and making it easier for people like us to get the updates. Considering their efforts, Twitter stepped forward to support them and help them in gathering news more efficiently.
Best Twitter accounts to follow during the pandemic
Twitter can help you out in many ways to overcome the stress of the isolation or to pas days of being quarantined. To those who are looking for authentic accounts to grab information and updated about the pandemic, they must follow the below-listed accounts.
If you want to seek professional advice about the common health issues you are experiencing you can get the updates from the account of David Juurlink. He explains and talks about the symptoms and ways to prevent them.
Apart from all of these accounts, the organizations are also contributing to connecting with the people. You can also opt for the U.S. FDA Twitter handle.
If you want to kill your time, you can find some great entertaining accounts as well. Like the one of Tret Andrew who is literally sharing his day’s updates with the followers connecting with them after every few hours. Or you can tune in to the house party session of Z THE DOM and stir more fun to your day.
Whether it’s about Twitter or any other platform, efforts are being made to prevent the Coronavirus outbreak and guide people to stay calm and prepared to handle any healthcare urgency. With such unparalleled efforts of every platform and organization, the world will soon be free from the havocs of this COVID-19 pandemic.
The post How Twitter is contributing to support masses during the Coronavirus outbreak appeared first on Search Engine Watch.
Twitter today updated its Developer Policy to clarify rules around data usage, including in academic research, as well as its position on bots, among other things. The policy has also been entirely rewritten in an effort to simplify the language used and make it more conversational, Twitter says. The new policy has been shortened from eight sections to four, and the accompanying Twitter Developer Agreement has been updated to align with the Policy changes, as well.
One of the more notable updates to the new policy is a change to the rules to better support non-commercial research.
Twitter data is used to study topics like spam, abuse and other areas related to conversation health, the company noted, and it wants these efforts to continue. The revised policy now allows the use of the Twitter API for academic research purposes. In addition, Twitter is simplifying its rules around the redistribution of Twitter data to aid researchers. Now, researchers will be able to share an unlimited number of Tweet IDs and/or User IDs, if they’re doing so on behalf of an academic institution and for the sole purpose of non-commercial research, such as peer review, says Twitter.
The company is also revising rules to clarify how developers are to proceed when the use cases for Twitter data change. In the new policy, developers are informed that they must notify the company of any “substantive” modification to their use case and receive approval before using Twitter content for that purpose. Not doing so will result in suspension and termination of their API and data access, Twitter warns.
The policy additionally outlines when and where “off-Twitter matching” is permitted, meaning when a Twitter account is being associated with a profile built using other data. Either the developer will need to obtain opt-in consent from the user in question, or they can only proceed if the information was provided by the person or is based on publicly available data.
The above changes are focused on ensuring Twitter data is accessible when being used for something of merit, like academic research, and that it’s protected from more questionable use cases.
Finally, the revamped policy clarifies that not all bots are bad. Some even enhance the Twitter experience, the company says, or provide useful information. As examples of good bots, Twitter pointed to the fun account @everycolorbot and informative @earthquakesSF.
Twitter identifies a bot as any account where behaviors like “creating, publishing, and interacting with Tweets or Direct Messages are automated in some way through our API.”
Going forward, developers must specify if they’re operating a bot account, what the account is, and who is behind it. This way, explains Twitter, “it’s easier for everyone on Twitter to know what’s a bot – and what’s not.”
Of course, those operating bots for more nefarious purposes — like spreading propaganda or disinformation — will likely just ignore this policy and hope not to be found out. This particular change follows the recent finding that a quarter of all tweets about climate change were coming from bots posting messages of climate change denialism. In addition, it was recently discovered that Trump supporters and QAnon conspiracists were using an app called Power10 to turn their Twitter accounts into bots.
Twitter says since it introduced a new developer review process in July 2018, it has reviewed over a million developer applications and approved 75%. It also suspended more than 144,000 apps from bad actors in the last six months and revamped its developer application to be easier to use. It’s now working on the next generation of the Twitter API and is continuing to explore new products, including through its testing program, Twitter Developer Labs.
India’s ruling party accused of running deceptive Twitter campaign to gain support for a controversial law
Bharatiya Janata Party, the ruling party in India, has been accused of running a highly deceptive Twitter campaign to trick citizens into supporting a controversial law.
First, some background: The Indian government passed the Citizenship Amendment Act (CAA) last month that eases the path of non-Muslim minorities from the neighboring Muslim-majority nations of Afghanistan, Bangladesh and Pakistan to gain Indian citizenship.
But, combined with a proposed national register of citizens, critics have cautioned that it discriminates against minority Muslims in India and chips away at India’s secular traditions.
Over the past few weeks, tens of thousands of people in the country — if not more — have participated in peaceful protests across the nation against the law. The Indian government, which has temporarily cut down internet access and mobile communications in many parts of India to contain the protests, has so far shown no signs of withdrawing the law.
On Saturday, it may have found a new way to gain support for it, however.
India’s Home Minister Amit Shah on Thursday tweeted a phone number, urging citizens to place a call to that number in “support of the CAA law.”
Thousands of people in India today, many affiliated with the BJP party, began circulating that phone number on Twitter with the promise that anyone who places a call would be offered job opportunities, free mobile data, Netflix credentials, and even company with “lonely women.”
The story of CAA support, in four pictures… pic.twitter.com/ueLNmqDRr8
— Meghnad (@Memeghnad) January 4, 2020
— SamSays (@samjawed65) January 4, 2020
— Netflix India (@NetflixIndia) January 4, 2020
Huffington Post India called the move latest “BJP ploy” to win support for its controversial law. BoomLive, a fact checking organization based in India, reported the affiliation of many of these people to the ruling party.
We have reached out to a BJP spokesperson and Twitter spokespeople for comment.
First time in 70 years that a legislation passed by Parliament needs huge rallies, promises of sex, jobs and Netflix accounts to drum up support.
— Rohini Singh (@rohini_sgh) January 4, 2020
If the allegations are true, this won’t be the first time BJP has used Twitter to aggressively promote its views. In 2017, BuzzFeed News reported that a number of political hashtags that appeared in the top 10 Twitter’s trends column in India were the result of organized campaigns.
Pratik Sinha, co-founder of fact-checking website Alt News, last year demonstrated how easy it was to manipulate many politicians in the country to tweet certain things after he gained accessed to a Google document of prepared statements and tinkered with the content.
Last month, snowfall in Kashmir, a highly sensitive region that hasn’t had internet connection for more than four months, began trending on Twitter in the U.S. It mysteriously disappeared after many journalists questioned how it made it to the list.
— Julia Carrie Wong (@juliacarriew) December 22, 2019
When we reached out, a Twitter spokesperson in India pointed TechCrunch to an FAQ article that explained how Trending Topics work. Nothing in the FAQ article addressed the question.
For about a year now, continuous integration and delivery service CircleCI has offered Orbs, a way to easily reuse commands and integrations with third-party services. Unsurprisingly, some of the most popular Orbs focus on AWS, as that’s where most of the company’s developers are either testing their code or deploying it. Today, right in time for AWS’s annual re:Invent developer conference in Las Vegas, the company announced that it has now added Orb support for the AWS Serverless Application Model (SAM), which makes setting up automated CI/CD platforms for testing and deploying to AWS Lambda significantly easier.
In total, the company says, more than 11,000 organizations started using Orbs since it launched a year ago. Among the AWS-centric Orbs are those for building and updating images for the Amazon Elastic Container Services and the Elastic Container Service for Kubernetes (EKS), for example, as well as AWS CodeDeploy support, an Orb for installing and configuring the AWS command line interface, an Orb for working with the S3 storage service and more.
“We’re just seeing a momentum of more and more companies being ready to adopt [managed services like Lambda, ECS and EKS], so this became really the ideal time to do most of the work with the product team at AWS that manages their serverless ecosystem and to add in this capability to leverage that serverless application model and really have this out of the box CI/CD flow ready for users who wanted to start adding these into to Lambda,” CircleCI VP of business development Tom Trahan told me. “I think when Lambda was in its earlier days, a lot of people would use it and they would use it and not necessarily follow the same software patterns and delivery flow that they might have with their traditional software. As they put more and more into Lambda and are really putting a lot more what I would call ‘production quality code’ out there to leverage. They realize they do want to have that same software delivery capability and discipline for Lambda as well.”
Trahan stressed that he’s still talking about early adopters and companies that started out as cloud-native companies, but these days, this group includes a lot of traditional companies, as well, that are now rapidly going through their own digital transformations.
A recently granted patent from Google is about supporting querying and predictions, and it does this by focusing on user-specific knowledge graphs.
Those User Specific Knowledge Graphs can be specific to particular users.
This means Google can use those graphs to provide results in response to one or more queries submitted by the user, and/or to surface data that might be relevant to the user.
I was reminded of another patent that I recently wrote about when I saw this patent, in the post Answering Questions Using Knowledge Graphs, where Google may perform a search on a question someone asks, and build a knowledge graph from the search results returned, to use to find the answer to their question.
So Google doesn’t just have one knowledge graph but may use many knowledge graphs.
New ones for questions that may be asked, or for different people asking those questions.
This User-Specific Knowledge Graph patent tells us that innovative aspects of the process behind it include:
- Receiving user-specific content
- The user-specific content can be associated with a user of one or more computer services
- That user-specific content is processed using one or more parsers to identify one or more entities and one or more relationships between those entities
- A parser being specific to a schema, and the one or more entities and the one or more relationships between entities being identified based on the schema
- This processes provides one or more user-specific knowledge graphs
- A user-specific knowledge graph being specific to the user, which includes nodes and edges between nodes to define relationships between entities based on the schema
- The process includes storing the one or more user-specific knowledge graphs
Optional Features involving providing one or more user-specific knowledge graphs may also include:
- Determining that a node representing an entity of the one or more entities and an edge representing a relationship associated with the entity are absent from a user-specific knowledge graph
- Adding the node and the edge to the user-specific knowledge graph
- The edge connecting the node to another node of the user-specific knowledge graph
Actions further include:
- Receiving a query
- Receiving one or more user-specific results that are responsive to the query
- The one or more user-specific results are provided based on the one or more user-specific knowledge graphs
- Providing the one or more user-specific results for display to the user
- An edge is associated with a weight
- The weight indicating a relevance of a relationship represented by the edge
- A value of the weight increases based on reinforcement of the relationship in subsequent user-specific content
- A value of the weight decreases based on lack of reinforcement of the relationship in subsequent user-specific content
- A number of user-specific knowledge graphs are provided based on the user-specific content
- Each user-specific knowledge graph being specific to a respective schema
- The user-specific content is provided through use of the one or more computer-implemented services by the user
Advantages of Using the User-Specific Knowledge Graph System
The patent describes the advantages of implementing the process in this patent:
- Enables knowledge about individual users to be captured in a structured manner
- Enabling results to be provided in response to complex queries, e.g., series of queries, regarding a user
- The user-specific knowledge graph may provide a single canonical representation of the user based on user activity inferred from one or more computer-implemented services
- User activities could be overlapping, where reconciliation of the user-specific knowledge graph ensures a canonical entry is provided for each activity
- Joining these together could lead to a universal knowledge graph, e.g., non-user-specific knowledge graph, and user-specific knowledge graphs
(That Universal Knowledge Graph sounds interesting.)
Information from sources like the following may be used to create User-Specific Knowledge Graphs:
- A user’s social network
- Social actions or activities
- A user’s preferences
- A user’s current location
This is so that content that could be more relevant to the user is used in those knowledge graphs.
We are told also that “a user’s identity may be treated so that no personally identifiable information can be determined for the user,” and that “a user’s geographic location may be generalized so that a particular location of a user cannot be determined.”
The User-specific Knowledge Graph Patent
This patent can be found at:
Structured user graph to support querying and predictions
Inventors: Pranav Khaitan and Shobha Diwakar
Assignee: Google LLC
US Patent: 10,482,139
Granted: November 19, 2019
Filed: November 5, 2013
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving user-specific content, the user-specific content being associated with a user of one or more computer-implemented services, processing the user-specific content using one or more parsers to identify one or more entities and one or more relationships between entities, a parser being specific to a schema, and the one or more entities and the one or more relationships between entities being identified based on the schema, providing one or more user-specific knowledge graphs, a user-specific knowledge graph being specific to the user and including nodes and edges between nodes to define relationships between entities based on the schema, and storing the one or more user-specific knowledge graphs.
What Content is in User-Specific Knowledge Graphs?
The types of services that user-specific knowledge graph information could be pulled from can include:
- A search service
- An electronic mail service
- A chat service
- A document sharing service
- A calendar sharing service
- A photo sharing service
- A video sharing service
- Blogging service
- A micro-blogging service
- A social networking service
- A location (location-aware) service
- A check-in service
- A ratings and review service
A User-Specific Knowledge Graph System
This patent describes a search system that includes a user-specific knowledge graph system as part of that search system, either directly connected to or connected to search system over a network.
The search system may interact with the user-specific knowledge graph system to create a user-specific knowledge graph.
That user-specific knowledge graph system may provide one or more user-specific knowledge graphs, which can be stored in a data store.
Each user-specific knowledge graph is specific to a user of the one or more computer-implemented services, e.g., search services provided by the search system.
The search system may interact with the user-specific knowledge graph system to provide one or more user-specific search results in response to a search query.
Structured User Graphs For Querying and Predictions
A user-specific knowledge graph is created based on content associated with the user.
These user-specific knowledge graphs include a number of nodes and edges between nodes.
A node represents an entity and an edge represents a relationship between entities.
Nodes and/or entities of a user-specific knowledge graph can be provided based on the content associated with a respective user, to which the user-specific knowledge graph is specific.
User-Specific Knowledge Graphs and Schemas
The user-specific knowledge graphs can be created based on one or more schemas (examples follow). A schema describes how data is structured in the user-specific knowledge graph.
A schema defines a structure for information provided in the graph.
A schema structures data based on domains, types, and properties.
A domain includes one or more types that share a namespace.
A namespace is provided as a directory of uniquely named objects, where each object in the namespace has a unique name or identifier.
For example, a type denotes an “is a” relationship about a topic, and is used to hold a collection of properties.
A topic can represent an entity, such as a person, place or thing.
Each of these topics can have one or more types associated with them.
A property can be associated with a topic and defines a “has a” relationship between the topic and a value of the property.
In some examples, the value of the property can include another topic.
A user-specific knowledge graph can be created based on content associated with a respective user.
That content may be processed by one or more parsers to populate the user-specific structured graph.
A parser may be specific to a particular schema.
Confidence or Weights in Connections
Weights that are assigned between nodes indicate a relative strength in the relationship between nodes.
The weights can be determined based on the content associated with the user, which content underlies provision of the user-specific knowledge graph.
That content can provide a single instance of a relationship between nodes, or multiple instances of a relationship between nodes.
So, there can be a minimum value and a maximum value.
Weights can also be dynamic:
- Varying over time based on content associated with the user
- Based on content associated with the user at a first time
- Based on content or a lack of content associated with the user at a second time
- The content at the first time can indicate a relationship between nodes
- Weights can decay over time
Multiple User Specific Knowledge Graphs
More than one user-specific knowledge graph can be provided for a particular user.
Each user-specific knowledge graph may be specific to a particular schema.
Generally, a user-specific knowledge graph includes knowledge about a specific user in a structured manner. (It represents a portion of the user’s world through content associated with the user through one or more services.)
Knowledge captured in the user-specific knowledge graph can include things such as:
- Social connections, e.g., real-world and/or virtual
- General likes
- General dislikes
User-Specific Knowledge Graph Versus User-Specific Social Graph
A social graph contains information about people who someone might be connected to, where a user-specific Knowledge graph also overs knowledge about those connections, such as shared activities between people who might be connected in a knowledge graph.
Examples of Queries and User-Specific Knowledge Graphs
These are examples from the patent. Note that searches, emails, social network posts may all work together to build a user-specific Knowledge Graph as seen in the combined messages/actions below, taken together, which may cause the weights on edges between nodes to become stronger, and nodes and edges to be added to that knowledge graph.
Example search query: [playing tennis with my kids in mountain view] to a search service
Search results: which may provide information about playing tennis with kids in Mountain View, Calif.
Nodes can be provided, with one representing the entity “Tennis,” one representing “Mountain View,” one representing “Family,” and a couple more each representing “Child.”
An edge can be provided that represents a “/Location/Play_In” relationship between the nodes, another edge may represent a “/Sport/Played_With” relationship between the nodes and other edges may represent “/Family/Member_Of” relationships between the node and the nodes.
Weights may be generated for each of the edges to represent different values as well.
A Person may post the example post “We had a great time playing tennis with our kids today!” in a social networking service, associated with geo-location data indicating Mountain View, Calif.
Nodes may be identified representing tennis, Mountain View, family and children, and edges between those nodes.
Weights may be generated between those edges.
Someone may receive an electronic message from a hotel, which says “Confirming your hotel reservation in Waikiki, Hi. from Oct. 15, 2014, through Oct. 20, 2014. We’re looking forward to making your family’s vacation enjoyable!”
Nodes can be added to the user-specific Knowledge graph, where those nodes represent the entities “Vacation” and “Waikiki”
Edges can be created in the user-specific knowledge graph in response to that email that represents a “/Vacation/Travelled_With” relationship between the nodes, one that represents a “/Vacation/CityTown” relationship between the nodes, and another edge that represents a “/Vacation/CityTown” relationship between the nodes.
Timing nodes may also be associated with the other nodes, such as a timing node representing October 2014, or a node representing a date range of Oct. 15, 2014, through Oct. 20, 2014.
The user can submit the example search query [kids tennis lessons in waikiki] to a search service.
Nodes may be created in the user-specific knowledge graph representing tennis, Waikiki, family, and children, as well as respective edges between at least some of the nodes.
That example search query may reinforce the relevance of the various entities and the relationships between the entities to the particular user.
That reinforcement may cause the respective weights associated with the edges to be increased.
The user can receive an email from a tennis club, which can include “Confirming tennis lessons at The Club of Tennis, Waikiki, Hi.”
Nodes represent tennis, and Waikiki, and the edges between them.
That email reinforces the relevance of the entities and the relationships between the entities to the particular user.
The weights between the entities could be increased, and a node could be added to represent the entity “The Club of Tennis,” which could then be connected to one or more other nodes.
User-Specific Knowledge Graphs Takeaways
This reminds me of personalized search, but tells us that it is looking at more than just our search history – It includes data from sources such as emails that we might send or receive, or posts that we might make to social networks. This knowledge graph may contain information about the social connections we have, but it also contains knowledge information about those connections as well. The patent tells us that personally identifiable information (including location information) will be protected, as well.
And it tells us that User-specific knowledge graph information could be joined together to build a universal knowledge graph, which means that Google is building knowledge graphs to answer specific questions and for specific users that could potentially be joined together, to enable them to avoid the limitations of a knowledge graph based upon human-edited sources like Wikipedia.
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When consumers need to find the right product, service or storefront for their needs, they grab their phone, jump on their laptop, or just say, Hey Siri, Hey Alexa, and Hey Cortana. Search results immediately populate their screen and they skim, select, learn, and go.
To win at the game of search, your small or medium-sized business needs to be present online, discoverable and well-matched to the specific needs of consumers. Easier said than done, right?
If you want to quickly reach a targeted audience, drive the right kind of traffic towards your website, and develop a marketing strategy that works alongside your SEO efforts, pay per click (PPC) advertising is a great option. When consumers perform high commercial intent searches, meaning they’re online with the intent to buy a specific product, paid ads get 65% of all clicks. It’s a very effective way to get your products front and center on the search page. Both Microsoft Advertising (formerly Bing Ads) and Google Ads offer pretty intuitive platforms when it comes to the account set-up and refinement, but if you’re not a marketing expert (and even if you are) you’re going to need a little help sometimes.
As a small business, you may not have time to really dig into PPC advertising, but you still care about building a campaign that works for you and for your potential customers. Or, maybe you have a strong handle on PPC, but you’re wondering what you could be doing better. Both these scenarios, and many more, could be helped by reaching out to your Microsoft Advertising or Google Ads customer support center or setting up an appointment with a PPC coach.
A coach? Yes, a coach. Really, try it. Working with PPC customer support at Microsoft Advertising, for example, can help your business get the right advice, employ the right tactics, and simply streamline the process, so you aren’t emerging from a PPC rabbit hole feeling frustrated and upset. That’s no fun and can be easily remedied. Here are five common concerns and how customer support can help small businesses like yours with their PPC campaigns.
“I have no idea how to get started.”
Sometimes when people jump into the world of PPC advertising, the process begins easily enough, but issues tend to pop up. Maybe you aren’t sure about how to establish a budget or conduct important keyword research. That’s ok, nobody expects you to be an expert right out of the gate.
Onboarding specialists are part of customer support and work with small businesses to set up your PPC ad account from scratch, create your first set of ads, research keywords, set a budget, and assist you with competitive bids. They view the entire process as a team effort and are genuinely interested in understanding your business goals and objectives. Then they help you design a PPC campaign to meet them.
“I can’t figure out why my campaigns aren’t performing.”
Coaches and customer support specialists can provide visibility on what is and isn’t working by showing businesses how to generate and understand a variety of performance reports. With over 30 different types of reports available, selecting and analyzing them on your own can be a little overwhelming at first, simply due to the sheer volume of data at our fingertips. Working with a coach can help provide clarity, and together you can identify relevant strategies and innovations that have a positive impact on your campaigns. In other words, they can help you figure out what all the data means and how to use it to your advantage.
If you’ve been using PPC advertising for quite a while, coaches can support your campaign by introducing you to the latest features and tools you may not know about. Sometimes we get into a routine and performance plateaus but talking to an expert for 15 minutes can totally refresh your PPC perspective and provide you with valuable insight and ideas.
“I’m afraid I’ll look like an idiot if I can’t figure this out on my own.”
Managing PPC campaigns is a learned skill, but it might not be something that comes naturally to you. A coach’s job isn’t to do everything for you, but to educate you on how to improve campaign performances on your own. Customer support can help business owners get familiar with PPC tools, processes and resources that help you successfully manage your ads without external support. The goal is to empower businesses with the know-how, competence, and confidence to handle their campaigns like a pro and troubleshoot any issues that come up. Learning, in and of itself, represents a measurement of success and makes the next PPC campaign easier to set up, more profitable, and effective.
“I don’t think customer support will understand anything about my business and it’s too much of a hassle. I just have to figure this out on my own.”
The whole point of customer support is to take the time to understand your industry and your business goals, that’s the only way to provide meaningful and targeted guidance. Coaches treat you like a partner and pro-actively offer strategic direction and the right tools to increase your PPC efficiency. They meet you at your level of expertise and build up from there, no matter your budget or your business. You need to be willing to share your story and reflectively consider what you want to get out of your various campaigns, but rest assured, if you’re willing to put in the time, it will most definitely not be wasted.
“I’m not sure I’m managing my campaign correctly and spend too much time worrying about it.”
This is a big one, especially for businesses that aren’t familiar with paid search. Your time is spent worrying that you’re doing it wrong instead of learning how to do it right. This is where working with a coach can really help because they provide you with peace of mind. Peace of mind in the information you’re using, your level of comfort and familiarity with the platform, and the belief that you are fully capable of making changes that improve your business’s visibility and lead conversions.
The OpenStack project, which powers more than 75 public and thousands of private clouds, launched the 19th version of its software this week. You’d think that after 19 updates to the open-source infrastructure platform, there really isn’t all that much new the various project teams could add, given that we’re talking about a rather stable code base here. There are actually a few new features in this release, though, as well as all the usual tweaks and feature improvements you’d expect.
While the hype around OpenStack has died down, we’re still talking about a very active open-source project. On average, there were 155 commits per day during the Stein development cycle. As far as development activity goes, that keeps OpenStack on the same level as the Linux kernel and Chromium.
Unsurprisingly, a lot of that development activity focused on Kubernetes and the tools to manage these container clusters. With this release, the team behind the OpenStack Kubernetes installer brought the launch time for a cluster down from about 10 minutes to five, regardless of the number of nodes. To further enhance Kubernetes support, OpenStack Stein also includes updates to Neutron, the project’s networking service, which now makes it easier to create virtual networking ports in bulk as containers are spun up, and Ironic, the bare-metal provisioning service.
All of that is no surprise, given that according to the project’s latest survey, 61 percent of OpenStack deployments now use both Kubernetes and OpenStack in tandem.
The update also includes a number of new networking features that are mostly targeted at the many telecom users. Indeed, over the course of the last few years, telcos have emerged as some of the most active OpenStack users as these companies are looking to modernize their infrastructure as part of their 5G rollouts.
Besides the expected updates, though, there are also a few new and improved projects here that are worth noting.
“The trend from the last couple of releases has been on scale and stability, which is really focused on operations,” OpenStack Foundation executive director Jonathan Bryce told me. “The new projects — and really most of the new projects from the last year — have all been pretty oriented around real-world use cases.”
The first of these is Placement. “As people build a cloud and start to grow it and it becomes more broadly adopted within the organization, a lot of times, there are other requirements that come into play,” Bryce explained. “One of these things that was pretty simplistic at the beginning was how a request for a resource was actually placed on the underlying infrastructure in the data center.” But as users get more sophisticated, they often want to run specific workloads on machines with certain hardware requirements. These days, that’s often a specific GPU for a machine learning workload, for example. With Placement, that’s a bit easier now.
It’s worth noting that OpenStack had some of this functionality before. The team, however, decided to uncouple it from the existing compute service and turn it into a more generic service that could then also be used more easily beyond the compute stack, turning it more into a kind of resource inventory and tracking tool.
Then, there is also Blazer, a reservation service that offers OpenStack users something akin to AWS Reserved Instances. In a private cloud, the use case for a feature is a bit different, though. But as some of the private clouds got bigger, some users found that they needed to be able to guarantee resources to run some of their regular, overnight batch jobs or data analytics workloads, for example.
As far as resource management goes, it’s also worth highlighting Sahara, which now makes it easier to provision Hadoop clusters on OpenStack.
In previous releases, one of the focus areas for the project was to improve the update experience. OpenStack is obviously a very complex system, so bringing it up to the latest version is also a bit of a complex undertaking. These improvements are now paying off. “Nobody even knows we are running Stein right now,” Vexxhost CEO Mohammed Nasar, who made an early bet on OpenStack for his service, told me. “And I think that’s a good thing. You want to be least impactful, especially when you’re in such a core infrastructure level. […] That’s something the projects are starting to become more and more aware of but it’s also part of the OpenStack software in general becoming much more stable.”
As usual, this release launched only a few weeks before the OpenStack Foundation hosts its bi-annual Summit in Denver. Since the OpenStack Foundation has expanded its scope beyond the OpenStack project, though, this event also focuses on a broader range of topics around open-source infrastructure. It’ll be interesting to see how this will change the dynamics at the event.
Last November, Facebook launched Instant Games, a new platform for gaming with friends inside the Messenger chat app. Today, the company is announcing a couple of notable new features for this gaming platform, including support for live streaming via Facebook Live and video chatting with fellow gamers. The idea with Instant Games is to boost people’s time spent in Messenger by giving… Read More
Social – TechCrunch
The iPhone 8, iPhone 8 Plus and iPhone X all support wireless charging using the Qi standard. It means that iPhones are now compatible with hundreds of chargers out there. But iPhone Qi charging is currently limited to 5W, or the slowest wireless charging speed. Apple is currently working on iOS 11.2 — this update is going to support 7.5W charging.
Wireless charging is nice if you… Read More
Today we are excited to be the first supporting vendor to announce a new service, Google’s AMP Client ID API, that will enable the same benefits for AMP pages displayed via Google surfaces. In May of this year we launched a solution to help you better understand your customers’ journeys across AMP and non-AMP experiences that were hosted on your own domain. Google’s AMP Client ID API will enable the same benefits for AMP pages displayed by Google such as in Google Search.
How will this work?
This solution works by allowing your web pages, which may be partially served on Google platforms and partially on your domain, to communicate with each other. This communication happens via a newly introduced Google API and with Google Analytics such that it can understand if a user on your non-AMP pages had ever visited an AMP page displayed by Google. When true, Google Analytics can help you understand user behavior across these two page types as a single cohesive experience.
To get started you’ll have to opt-in to this solution via a code change. The small code change is required on both your AMP and non-AMP websites to enable this as well as an acknowledgement of the new Google Analytics terms for usage of this API.
When will this happen?
The ability to opt-in to this solution is available today and you can find code instructions and new terms here. Please review the documentation and opt-in when you are ready.
Are there any other implications of this change?
Once you opt-in to this solution you will notice changes to some of your metrics. Your user and session metrics will drop down to more accurate counts as formerly distinct users are recognised as the same person, as well as related metrics that will also become more accurate (such as Time on Site and Bounce Rate). And New Users may rise temporarily. This is a function of the product more accurately counting your users. It’s a one-time effect that will continue until all your users who have viewed AMP pages in the past return to your site (this can take a short or long period of time depending on how quickly your users return to your site/app). To get more detail about what may change, please read our help center article.
Opt into this new feature today to get deeper insight into how users are interacting with your AMP pages.
Posted by the Google Analytics team
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