Three quarters of Facebook users are unaware that the social network lists their personal interests and traits for advertisers, according to new research. A study published by Pew Research Center revealed the scale of Facebook users' ignorance when it comes to how the tech giant uses their data to make money. Facebook consistently claims that it is transparent in its data collection practices, making it possible for people to find out how its algorithm categorises their interests via the'Your ad preferences' page. But the research suggests that most users are unaware of this. In a survey of 963 US adults, 74 per cent said they did not know Facebook maintained lists of their interests and 51 per cent said they are not comforable with Facebook compiling this information.

A Deloitte article says government agencies seeking to generate insights from unstructured data to facilitate the decision-making process and policy analysis could use artificial intelligence in the form of natural language processing. NLP has seven technical capabilities that could help agencies identify patterns, analyze public opinion and categorize topics, according to the article published Wednesday. Those capabilities are topic modeling; text categorization; text clustering; information extraction; named entity resolution; relationship extraction; and sentiment analysis. NLP could help address several issues across defense and national security, health care, energy and financial services domains and those issues include analyzing public feedback and improving regulatory compliance and predictions. The article cited how the Defense Advanced Research Projects Agency uses NLP in the Deep Exploration and Filtering of Text program to glean insights from data.

As a data science engineer, I found one of the most challenging task is Text Analytics. Natural language processing is one the cutting edge technology to talk with computers .

With this short article I hope to be able to give some clarifications about the "BITCOIN TWITTER Sentiment Analysis" automatic posts that we publish every day both here, and on steemit.com.

People around the globe are more actively using social media platform such as Twitter, Facebook, and Instagram etc. They share information, opinions, ideas, experiences and other details in the social media. The business communities have become more aware of these developments and they want to use the available information in their favor. One of the ways to understand the people opinions on the product they are using is by collecting tweets related to those products. Then performing the sentiment analysis on the tweets collected on a particular topic.

I'm back this semester as a DH Prototyping Fellow, and together, Alyssa Collins and I are working on a project titled "Twitterature: Methods and Metadata." Specifically, we're hoping to develop a simple way of using Twitter data for literary research. The project is still in its early stages, but we've been collecting a lot of data and are now beginning to visualize it (I'm particularly interested in the geolocation of tweets, so I'm trying out a few mapping options). In this post, I want to layout our methods for collecting Twitter data. Okay, Alyssa and I have been using a python based Twitter scraping script, which we modified to search Twitter without any time limitations (the official Twitter search function is limited to tweets of the past two weeks). So, to run the Twitter scraping script, I entered the following in my command line: python3 TwitterScraper.py.

Here a sentiment analysis based on the tweets published today 22-12-2018 so far about BITCOIN. The program analyzed 373 Tweets from midnight until now 05:54:16, and labeled 301 as SPAM or USELESS, and 72 as decent QUALITY or USEFUL. Our Artificial Intelligence for sentiment analysis, marked 3 tweets as Angry, 0 as Fear, 0 as Bored, 0 as Sarcasm, 13 as Excited, 0 as Sad, and 11 as Happy. Human group capped bitcoin at 21 million and therefore they can uncap it. Bitcoin is NO different from any human imagination creation.

Python is a high-level, object-oriented development tool. Here is a quick, hands-on tutorial on how to use the text analytics function. Let's begin by understanding some of the NLP features of Python, how it is set up and how to read the file used for: Let's move a step deeper and understand the four basics of NLP in detail: N-grams is a sequence of words n items long. 'mango is my favorite fruit.',

E-commerce has become more popular with the growth in internet and network technologies. Many people feel convenient to buy products online using various forums such as Amazon, Flipchart, Awok etc. When customers buy the products online there is an option for them to provide their review comments. Many customers chose to provide their experience, opinion, feedback etc. Such product reviews are rich in information consisting of feedback shared by users.

Surveying the reactions to the latest revelation that Facebook played fast and loose with user data, it was hard not to harken back to what Scott McNally, the founding CEO of Sun Microsystems, told a group of reporters, including one from WIRED, in 1999: "You have zero privacy anyway. McNealy was widely excoriated for candor, but nearly twenty years later, we appear to be not only fighting the same fight but continually shocked that McNally's words, so jarring then, remain so true now. Zachary Karabell is a WIRED contributor and president of River Twice Research. This past spring, when it was revealed Facebook allowed campaign data-mining firm Cambridge Analytica to target users, it was grandly described as "Facebook's Privacy Crisis." When Facebook disclosed in September that hackers accessed the data of 30 million Facebook users, the massive breach that threw the public into a panic, prompting Facebook to assure the masses with messages that "Your privacy and security are important to us." And then, a few weeks later, when reports found that Facebook allowed select companies to access user posts and contact information without clear consent, commentary after commentary described this as "Yet Another Massive Privacy Scandal."