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✅ What is Machine Learning ?

Machine learning is a type of artificial intelligence (AI) that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. The basic premise of machine learning is to build algorithms that can receive input data and use statistical analysis to predict an output value within an acceptable range.

Machine learning algorithms are often categorized as being supervised or unsupervised. Supervised algorithms require humans to provide both input and desired output, in addition to furnishing feedback about the accuracy of predictions during training. Once training is complete, the algorithm will apply what was learned to new data. Unsupervised algorithms do not need to be trained with desired outcome data. Instead, they use an iterative approach called deep learning to review data and arrive at conclusions. Unsupervised learning algorithms are used for more complex processing tasks than supervised learning systems.

The processes involved in machine learning are similar to that of data mining and predictive modeling. Both require searching through data to look for patterns and adjusting program actions accordingly. Many people are familiar with machine learning from shopping on the internet and being served ads related to their purchase. This happens because recommendation engines use machine learning to personalize online ad delivery in almost real time. Beyond personalized marketing, other common machine learning use cases include fraud detection, spam filtering, network security threat detection, predictive maintenance and building news feeds.

Facebook's News Feed, for example, uses machine learning to personalize each member's feed. If a member frequently stops scrolling to read or "like" a particular friend's posts, the News Feed will start to show more of that friend's activity earlier in the feed. Behind the scenes, the software is simply using statistical analysis and predictive analytics to identify patterns in the user's data and use those patterns to populate the News Feed. Should the member no longer stop to read, like or comment on the friend's posts, that new data will be included in the data set and the News Feed will adjust accordingly.

✅ What is Opinion or Sentiment Mining ?

Opinion mining is a type of natural language processing for tracking the mood of the public about a particular product.

Opinion mining, which is also called sentiment analysis, involves building a system to collect and categorize opinions about a product. Automated opinion mining often uses machine learning, a type of artificial intelligence (AI), to mine text for sentiment.

Opinion mining can be useful in several ways. It can help marketers evaluate the success of an ad campaign or new product launch, determine which versions of a product or service are popular and identify which demographics like or dislike particular product features. For example, a review on a website might be broadly positive about a digital camera, but be specifically negative about how heavy it is. Being able to identify this kind of information in a systematic way gives the vendor a much clearer picture of public opinion than surveys or focus groups do, because the data is created by the customer.

There are several challenges in opinion mining. The first is that a word that is considered to be positive in one situation may be considered negative in another situation. Take the word "long" for instance. If a customer said a laptop's battery life was long, that would be a positive opinion. If the customer said that the laptop's start-up time was long, however, that would be is a negative opinion. These differences mean that an opinion system trained to gather opinions on one type of product or product feature may not perform very well on another.

A second challenge is that people don't always express opinions the same way. Most traditional text processing relies on the fact that small differences between two pieces of text don't change the meaning very much. In opinion mining, however, "the movie was great" is very different from "the movie was not great".

Finally, people can be contradictory in their statements. Most reviews will have both positive and negative comments, which is somewhat manageable by analyzing sentences one at a time. However, the more informal the medium (twitter tweets or blog posts for example), the more likely people are to combine different opinions in the same sentence. For example: "the movie bombed even though the lead actor rocked it" is easy for a human to understand, but more difficult for a computer to parse. Sometimes even other people have difficulty understanding what someone thought based on a short piece of text because it lacks context. For example, "That movie was as good as his last one" is entirely dependent on what the person expressing the opinion thought of the previous film.

See also: data mining, text mining

✅ What is Social Media Analytics ?

Social media analytics is the practice of gathering data from social media websites and analyzing that data using social media analytics tools to make business decisions. The most common use of social media analytics is to mine customer sentiment to support marketing and customer service activities.

The first step in a social media intelligence initiative is to determine which business goals the data that is gathered and analyzed will benefit. Typical objectives include increasing revenues, reducing customer service costs, getting feedback on products and services, and improving public opinion of a particular product or business division.

Once the business goals have been identified, businesses should define key performance indicators (KPIs) to objectively evaluate the business analytics data.

Metrics to track

Business metrics derived from social media analytics may include customer engagement, which could be measured by the number of followers for a Twitter account and number of retweets and mentions of a company's name. With social media monitoring, businesses can also look at how many people follow their presence on Facebook and the number of times people interact with their social profile by sharing or liking their posts.

More advanced types of social media analysis involve sentiment analytics. This practice involves sophisticated natural-language-processing machine learning algorithms parsing the text in a person's social media post about a company to understand the meaning behind that person's statement. These algorithms can create a quantified score of the public's feelings toward a company based on social media interactions and give reports to management on how well the company interacts with customers.

Popular tools

There are a number of types of social media analytics tools for analyzing unstructured data found in tweets and Facebook posts. In addition to text analysis, many enterprise-level social media analytics tools will harvest and store the data. Some of these tools come from niche players, while more traditional enterprise analytics software vendors offer packages dedicated to social media intelligence.

As more social media analytics rely on machine learning, popular open platforms like R, Python and TensorFlow serve as social media analytics tools.

Importance of social media analytics

There is a tremendous amount of information in social media data. In decades past, enterprises paid market research companies to poll consumers and conduct focus groups to get the kind of information that consumers now willingly post to public social media platforms.

The problem is this information is in the form of free text and natural language, the kind of unstructured data that analytics algorithms have traditionally. But as machine learning and artificial intelligence have advanced, it's become easier for businesses to quantify in a scalable way the information in social media posts.

This allows enterprises to extract information about how the public perceives their brand, what kind of products consumers like and dislike and generally where markets are going. Social media analytics makes it possible for businesses to quantify all this without using less reliable polling and focus groups.

✅ What is Pinterest ?

Pinterest is a social curation website for sharing and categorizing images found online.

The site is described in its own content as a visual bookmarking site. Pinterest is a portmanteau of the words “pin” and “interest.”

Pinterest categories include architecture, art, DIY and crafts, fashion, food and drink, home décor, science and travel, among an almost endless list of other possibilities. Users can add a “Pin it” button to their browser and then select and “pin” online images to virtual pinboards, which are used to organize categories. Pinterest requires brief descriptions but the main focus of the site is visual. Clicking on an image will take you to the original source, so, for example, if you click on a picture of a pair of shoes, you might be taken to a site where you can purchase them. An image of blueberry pancakes might take you to the recipe; a picture of a whimsical birdhouse might take you to the instructions. Users can browse or search for image content and can follow the boards of other users and can “like” or repin other users’ pins.

Pinterest was founded by Ben Silbermann, Paul Sciarra and Evan Sharp. The Pinterest service launched as a closed beta in March 2010. Pinterest membership was initially by invitation-only but is now open to the general public. In 2011, TechCrunch selected Pinterest as the year’s top startup, and Time magazine named it as one of the top 50 websites of that year. As of January 2016, the site had over 100 million users on a monthly basis.

Silbermann pitched Pinterest as a "catalog of ideas" rather than a social networkingplatform, maintaining that the emphais is on empowering users to "go out and do that thing." Nevertheless, the site is one of the most popular social media websites. In January 2016, Alexa ranked Pinterest at #12 for most visted sites in the United States.

See a brief introduction to Pinterest:

✅ What is Reddit ?

Reddit is a social news website and forum where content is socially curated and promoted by site members through voting. The site name is a play on the words "I read it."

Reddit member registration is free, and it is required to use the website's basic features.

For a monthly fee or yearly subscription, redditors can upgrade to Reddit Gold. This service provides a set of extended features not available to nonpaying users. Features of Reddit Gold include access to members-only communities and the ability to turn off sidebar ads.

What are subreddits and how do they work?

The site is composed of hundreds of subcommunities, known as subreddits. Each subreddit has a specific topic, such as technology, politics or music. Reddit's homepage, or the front page, as it is often called, is composed of the most popular posts from each default subreddit. The default list is predetermined and includes subreddits such as "pics," "funny," "videos," "news" and "gaming."

Reddit site members, also known as redditors, submit content which is then voted upon by other members. The goal is to send well-regarded content to the top of the site's front page. Content is voted on via upvotes and downvotes: arrows on which users click to the left of a post. The more upvotes a post gets, the more popular it becomes, and the higher up it appears on its respective subreddit or the front page. To access a subreddit via the address bar, simply type "reddit.com/r/subreddit name."

How to use Reddit

Upon arriving on the site's front page, users will notice a list of posts -- a collection of text posts, link posts, images and videos. When logged out of a Reddit account, the front page is composed of the site's default subreddits -- a list of about 50 topics including music, videos, news and GIFs, among others. After creating an account, users will automatically be "subscribed" to the list of default subreddits. Users can then unsubscribe to any of the default subreddits they do not wish to view, and they can subscribe to additional subreddits to get a personalized front page of content that interests them.

Users can also comment on posts after creating an account. Commenting is one of Reddit's core features, and it is the primary way for users to interact with each other, besides private messaging. Comments, like posts, can be voted on by users and are then ranked accordingly. The comment with the highest number of votes sits at the top of the comment section and is referred to as the top comment.

Reddit company information

Reddit is similar to Digg, another user-generated social networking site. Steve Huffman and Alexis Ohanian started Reddit in 2005, and Condé Nast Publications acquired the site in October 2006. Reddit split from Condé Nast in 2011, and now operates under Advance Publications. A July 8, 2012, NYMag.com article reported that 35 million new users sign up for Reddit every month.

Since its inception, Reddit has been the subject of many controversies, some great enough to make the news.

Notable controversies

Since its inception, Reddit has been the subject of many controversies, some great enough to make the news.

Site statistics and user demographics

As of this writing, Reddit is the 24th most-visited website in the world and the 7th most-visited website in the United States, with the U.S. accounting for 46.9% of the site's visitors, according to web traffic data and analytics company Alexa Internet. According to a 2016 study by the Pew Research Center, 71% of Reddit's audience is composed of men.

Popular acronyms

Many acronyms are unique to Reddit. They are commonly found in post titles, subreddit rules and comments. The following is a breakdown of some of the most commonly used acronyms on the site.

ELI5: Explain like I'm 5 -- A term used when redditors want something explained to them in very simple terms, as if they were a five-year-old asking for the answer to a question. A popular subreddit, explainlikeimfive, exists for this very purpose.
TLDR or TL;DR: Too long; didn't read -- In some longer posts or comments, redditors may place a, "TLDR" at the end of their text for the purpose of shortening what they wrote if other redditors do not want to take the time to read the entire post.
NSFW: Not safe for work -- When redditors make a post or comment that has explicit content, it is marked with this acronym to let other redditors know not to view the content at work or any place where explicit material would be unsuitable.
TIL: Today I learned -- Used mainly in the form of "TIL" posts, this term is used when redditors want to share something new they learned.
OP: Original poster -- The redditor who created the initial post.
AMA: Ask me anything -- A popular acronym used on Reddit's "IAmA" subreddit, where redditors can post "AMA" threads. This is another name for a Q&A thread, where redditors answer questions about their life and, usually, their occupation. President Barack Obama made headlines when he participated in an AMA on Aug. 29, 2012. He was the first sitting president to do so.

✅ What is LinkedIn

LinkedIn is a social networking site designed specifically for the business community. The goal of the site is to allow registered members to establish and document networks of people they know and trust professionally.

A LinkedIn member’s profile page, which emphasizes skills, employment history and education, has professional network news feeds and a limited number of customizable modules. Basic membership for LinkedIn is free. Network members are called “connections.” Unlike other free social networking sites like Facebook or Twitter, LinkedIn requires connections to have a pre-existing relationship.

With basic membership, a member can only establish connections with someone he has worked with, knows professionally (online or offline) or has gone to school with. Connections up to three degrees away (see six degrees of separation) are seen as part of the member's network, but the member is not allowed to contact them through LinkedIn without an introduction. Premium subscriptions can be purchased to provide members with better access to contacts in the LinkedIn database.

LinkedIn was co-founded by Reid Hoffman, a former Executive Vice President in charge of business and corporate development for PayPal. The site, which was launched in May 2003, currently has over 300 million members from 200 countries, representing 170 industries. According to Reid Hoffman, 27 percent of LinkedIn subscribers are recruiters.

Microsoft acquired LinkedIn in June of 2016 for $26.2 billion. According to some experts, the rich troves of semi-structured data that LinkedIn's members freely give away -- job titles, geographies, industry information, skill sets -- made the deal a steal, even though the LinkedIn acquisition was Microsoft's more expensive purchase to date. LinkedIn has been gathering up data across the more than 225 million LinkedIn profiles in an Economic Graph to provide policymakers, employers, workers and educators with data-driven insight into patterns that will help align workforce supply with demand. Such patterns include when people generally look for the next step in their career, work migration trends in specific geographical locations, skill gaps in specific industries and what cities are "stickiest," i.e. areas that employees are less likely to move away from.

✅ What is Wikipedia ?

Wikipedia is a free, open content online encyclopedia created through the collaborative effort of a community of users known as Wikipedians. Anyone registered on the site can create an article for publication; registration is not required to edit articles. The site's name comes from wiki, a server program that enables anyone to edit Web site content through their Web browser.

Jimmy Wales and Larry Sanger co-founded Wikipedia as an offshoot of an earlier encyclopedia project, Nupedia, in January 2001. Originally, Wikipedia was created to provide content for Nupedia. However, as the wiki site became established it soon grew beyond the scope of the earlier project. As of January 2015, the website provided well over five million articles in English and more than that number in all other languages combined. At that same time, Alexa ranked Wikipedia as the seventh-most popular site on the Internet. Wikipedia was the only non-commercial site of the top ten.

Criticisms of Wikipedia include assertions that its openness makes it unreliable and unauthorative. Because articles don't include bylines, authors aren't publicly accountable for what they write. Similarly, because anyone can edit any article, the site's entries are vulnerable to unscrupulous edits. In August 2007, Virgil Griffiths created a site, WikiScanner, where users could track the sources of edits to Wikipedia entries. Griffiths reported that self-serving edits typically involved whitewashing or removal of criticism of a person or organization or, conversely, insertion of negative comments into the entry about a competitor. Wikipedia depends upon the vigilance of editors to find and reverse such changes to content.

In addition to the encyclopedia, the non-profit Wikipedia foundation oversees several other open-content projects, including: