Mining such data to determine how people feel about your product, brand, or service, is called Sentiment Analysis. When applied to social media channels, it can be used to identify spikes in sentiment, thereby allowing you to identify potential product advocates or social media influencers. Companies such as Microsoft, IBM and smaller emerging companies offer REST APIs that integrate easily with your existing software applications. For example, using the following publicly available Sentiment Analysis REST API from a small start-up called Social Opinion, we pass in the text, "this phone is awesome", to the following URL: In the response, we can see the text has been identified as expressing positive emotion, with a 64% probability of that being true.
"Text Analytics with Python" published by Apress\Springer, is a book packed with 385 pages of useful information based on techniques, algorithms, experiences and various lessons learnt over time in analyzing text data. Learn the techniques related to natural language processing and text analytics, and gain the skills to know which technique is best suited to solve a particular problem. Text Analytics with Python teaches you both basic and advanced concepts, including text and language syntax, structure, semantics. You will start with the basics of natural language and Python and move on to advanced analytical and machine learning concepts.
"American consumers continued to disagree with themselves in June as consumer confidence has remained high but has still not translated into much higher consumption," Eugenio Alemán, a senior economist at Wells Fargo Securities, wrote in a research note Friday. "Although personal consumption expenditures are expected to bounce back during the second quarter of the year, the bounce back may not be as strong as what we were expecting if these numbers remain as they were originally published, which is a big if."
"Rather than waiting for each adverse event to occur, CFSAN wanted to be aware of the precursors and try to prevent the incident." CFSAN subsequently started a centerwide Chemical Signal Detection program, led by the Signals Management Branch in the Office of Analytics and Outreach, leveraging expertise from all the program offices in the center. Since CFSAN did not have the human resources to review the vast volume of information this task entailed, it began looking into text analytics solutions. After a careful evaluation, CFSAN selected a suite of SAS technologies (SAS Enterprise Miner, SAS Text Miner, SAS Contextual Analysis and SAS Visual Analytics) and began piloting the research to build an "Emerging Chemical Hazard Intelligence Platform" (ECHIP).
Unless you've been living with the faceless men in Braavos, it's no surprise that Game of Thrones was the most-tweeted show of 2016. Wednesday morning, Twitter shared rankings of the show's most talked-about episodes, characters, and emoji. SEE ALSO: Sophie Turner claims she learned about sex from'Game of Thrones' scripts As Thrones fever rises over time, four of the five most-tweeted episodes ever were from Season 6, including the premiere, the finale, the infamous "Hold the door" episode, and the rigorous "Battle of the Bastards." And these were the most-tweeted hashtags from Season 6, which reflect general enthusiasm for the show and Jon Snow's pivotal resurrection: The three most followed "cast members" (you'll see why it's in quotes) on Twitter are: And if you're of the rare breed who don't care for Game of Thrones and would rather it not cloud your Twitter timeline on Sundays, Twitter has a handy little hack to mute words: Game of Thrones returns July 16 to turn Twitter into a glorious mess.
If you have a 4G plan with Virgin Mobile, you can now access Twitter without diving in to your monthly data allowance. It's a sensible strategy, given the popularity of Facebook, Twitter and WhatsApp in the UK. The Canadian Radio-television and Telecommunications Commission ruled against a "free" music streaming service offered by Videotron, given it created an "undue and unreasonable disadvantage" for services that weren't included in the plan. The FCC, meanwhile, has taken a different tack, dropping its investigations into zero-rating services offered by T-Mobile, AT&T and Verizon in the US.
As AWS continues to support the Artificial Intelligence (AI) community with contributions to Apache MXNet and the release of Amazon Lex, Amazon Polly, and Amazon Rekognition managed services, we are also expanding our team of AI experts, who have one primary mission: To lower the barrier to AI for all AWS developers, making AI more accessible and easy to use. At ISI, she spearheaded multimillion-dollar research grants funded by the Defense Advanced Research Projects Agency (DARPA) and Intelligence Advanced Research Projects Activity (IARPA). The research focused on topics such as machine reading, which aims at teaching machines to read and understand text just like humans do; information extraction from unstructured documents on the Web; metaphor interpretation; and sentiment analysis. Product Marketing Manager for the AWS AI portfolio of services which includes Amazon Lex, Amazon Polly, and Amazon Rekognition, as well the AWS marketing initiatives with Apache MXNet.
So having quick access to information is critical for making rational business decisions. BI is an umbrella term that refers to a variety of software applications used to analyze data and support a wide spectrum of business decisions, ranging from operational to strategic. Another promising area of NLP application in BI is sentiment analysis -- the use of natural language processing techniques to extract subjective information from a piece of text, also known as Opinion Mining. In our next article that will come soon we will review and compare the TOP Natural Language Processing APIs -- make sure not to miss it!