how twitter uses big data?
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Twitter's ranking algorithm has taken in lots of data, processed it through deep neural networks and learned over time what content would be relevant for each individual user. All tweets are scored on a ranking model that is used to determine the probability if a user would value that content in their feed.
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Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. Big data was originally associated with three key concepts: volume, variety, and velocity.
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Five Powerful Ways Data is Changing Our World. Big data has already started helping organizations to improve their bottom lines, gain agility, spot meaningful innovations, and transform businesses[4]. The data revolution has turned out an impetus for other enabling industries such as compute, storage, and network.
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Lists help you spend your time more effectively on Twitter because you can more easily find, monitor, and interact with the right people. Like any list, Twitter lists are practical and useful. This simple yet efficient feature allows you to easily group the people and brands you want to follow on Twitter.
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The only way to know for sure if someone has seen your Twitter is through direct engagement — a reply, a favorite or a retweet. That said, if a user wants to have a general idea about how many people have seen a tweet, then they can do so by visiting the Twitter Analytics page.
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As Twitter celebrates its 10th birthday today, @VENETHIS will send approximately his 37,771,000th tweet. He's by far the service's most prolific user, according to Twitter Counter, a statistics and analytics service powered by Twitter that tracks the accounts with the most tweets.
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Twitter allows its users to connect by following each other, while Facebook encourages users to add one another as friends. Both services also allow users to tag others in their posts, meaning that the post will appear in the tagged person's news feed. This is a key part of the content sharing process.
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Unlike with Facebook, there is actually a way to get some information on how many people are viewing your profile or your tweets. Go to Twitter's analytics page and log in with your Twitter account. You'll see something like this.
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Twitter requires people using the service to be 13 years of age or older. If you signed up for an account before you were 13 years old, and now meet our minimum age requirement, you can regain access to your account by removing some data.
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['Twitter History.', 'Gnip.', 'Magic Pony Technology.', 'MoPub Advertising Solutions.', 'Periscope.', 'TapCommerce.', 'TellApart.', 'TweetDeck.']
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Traditional database systems are based on the structured data i.e. traditional data is stored in fixed format or fields in a file. ... Big data uses the semi-structured and unstructured data and improves the variety of the data gathered from different sources like customers, audience or subscribers.
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Big data can provide information outside of a company's own data sources, serving as an expansive resource. Therefore, it is a component of business intelligence, offering a comprehensive view into your processes. Big data often constitutes the information which will lead to business intelligence insights.
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Simply put, no. There is no way for a Twitter user to know exactly who views their Twitter or specific tweets. ... That said, if a user wants to have a general idea about how many people have seen a tweet, then they can do so by visiting the Twitter Analytics page.
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A Retweet is a re-posting of a Tweet. Twitter's Retweet feature helps you and others quickly share that Tweet with all of your followers. You can Retweet your own Tweets or Tweets from someone else. Sometimes people type "RT" at the beginning of a Tweet to indicate that they are re-posting someone else's content.
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Social media has changed the way we communicate with each other by giving us the ability to be constantly communicating. A tweet can be shared with millions of people in an instant. A video can go viral on Facebook or YouTube in just minutes.
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Big data involves larger quantities of information while small data is, not surprisingly, smaller. Here's another way to think about it: big data is often used to describe massive chunks of unstructured information. Small data, on the other hand, involves more precise, bite-sized metrics.
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['Unorganized data. Big data is highly versatile. ... ', 'Data storage and retention. This is one of the most obvious risks associated with big data. ... ', 'Cost management. The process of storing, archiving, analyzing, reporting and managing big data involves costs. ... ', 'Incompetent analytics. ... ', 'Data privacy.']