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."

Even for a company as serially scandalous as Facebook, it's been a bad week for the social network. Separate investigations revealed that Facebook gave more than 150 firms access to people's private messages, while also making it impossible for users to avoid location-based ads. After months of fallout from the Cambridge Analytica scandal, US prosecutors also finally got around to filing a lawsuit against Facebook for its data sharing practices. Individually, none of these would likely be enough to bring Facebook down, but some experts believe that, collectively, this could signal the end for the internet behemoth. David Carroll, an associate professor at Parsons School of Design in New York, said this week may finally have dealt Facebook its "knockout" blow.

If there is one message Facebook has been trying to send to the world in 2018, it's that the company understands it needs to rethink the way it operates. Facebook says it understands that it must better police the content that appears on its platforms. And as a result of the Cambridge Analytica scandal early this year, Facebook says it must be more effective in how it protects user data, more transparent about all the data it collects, and more clear about who has access to the data. CEO and cofounder Mark Zuckerberg said fixing Facebook was his project for 2018, and he said earlier this year that he was dedicating enough resources to the problem that we should expect to see tangible progress as we approached 2019. Facts have proven to be inconvenient things for Facebook in 2018. Every month this year--and in some months, every week--new information has come out that makes it seem as if Facebook's big rethink is in big trouble.

We regret to inform you that we may have published our article titled "Facebook's terrible 2018" just a few hours too early. Tonight the New York Times has once again dug into the social network and assembled -- based on internal documents and interviews with employees, former employees and business partners --an unflattering picture of the data it has been sharing for years with the likes of Bing and Rotten Tomatoes. Taken as a whole, these revelations make the Cambridge Analytica data leak revelations seem almost insignificant. Even with the last few months and years of revelations, the behavior described is surprising -- and not just for users. According to the article, companies like Apple and Russian search giant Yandex claimed to not know how much access Facebook had given them to user information.