At least 11 popular apps are reportedly sharing people's sensitive data with Facebook, even if they don't have an account on the social network. The Wall Street Journal found that apps which can help track personal information such as body weight, menstrual cycles and pregnancy are sending such details to Facebook. The apps that were found to share personal data include Flo Period & Ovulation Tracker, BetterMe: Weight Loss Workouts, Breethe, Realtor.com and Instant Heart Rate: HR Monitor. The report suggests none of these apps had an option for users to prevent them from sharing personal data with Facebook, nor do they necessarily make it clear to people their data is making its way to Facebook's servers. The publication was only able to specifically decipher the types of data that iOS apps send Facebook, but a third-party test determined at least one Android fitness app shares weight and height data too.

Sentiment analysis is a task that may suffer from a lack of data in certain cases, as the datasets are often generated and annotated by humans. In cases where data is inadequate for training discriminative models, generate models may aid training via data augmentation. Generative Adversarial Networks (GANs) are one such model that has advanced the state of the art in several tasks, including as image and text generation. In this paper, I train GAN models on low resource datasets, then use them for the purpose of data augmentation towards improving sentiment classifier generalization. Given the constraints of limited data, I explore various techniques to train the GAN models. I also present an analysis of the quality of generated GAN data as more training data for the GAN is made available. In this analysis, the generated data is evaluated as a test set (against a model trained on real data points) as well as a training set to train classification models. Finally, I also conduct a visual analysis by projecting the generated and the real data into a two-dimensional space using the t-Distributed Stochastic Neighbor Embedding (t-SNE) method.

NLP is a technology through which computers can "understand" and reproduce human language. Although the language processing applications are in the early stage of development that isn't very mature yet, they are definitely one of the most interesting tools that might soon change the online space for good. NLP applications are mostly used in chat-bots and other tools providing virtual customer support. Of course, any interaction with customers is meticulously tracked, analysed and optimised to perform better and better. This itself makes the NLP technology a perfect tool for the sentiment analysis.

Where's the best place to look for free online datasets for NLP? We combed the web to create the ultimate cheat sheet, broken down into datasets for text, audio speech, and sentiment analysis. Sentiment140: a popular dataset, which uses 160,000 tweets with emoticons pre-removed. Twitter US Airline Sentiment: Twitter data on US airlines from February 2015, classified as positive, negative, and neutral tweets. Yelp Reviews: An open dataset released by Yelp, contains more than 5 million reviews.

German anti-trust authorities have ruled against Facebook over its methods of combining user data from different sources, including WhatsApp and Instagram. The Federal Cartel Office, or Bundeskartellamt said the firm was exploiting its position as a dominant social media company in violation of European regulations. Facebook, however, says this is not the case. In a statement issued after the ruling, Facebook said its data use is in compliance with GDPR and is intended to'protect people's safety and security.' German anti-trust authorities have ruled against Facebook over its methods of combining user data from different sources, including WhatsApp and Instagram.

Germany has ordered Facebook to curb its data collection practices in the country, after a ruling that the world's largest social media network abused its market dominance to gather information about users without their knowledge or consent. "In future, Facebook will no longer be allowed to force its users to agree to the practically unrestricted collection and assigning of non-Facebook data to their Facebook accounts," Federal Cartel Office chief Andreas Mundt said in the landmark order on Thursday. Facebook said it would appeal the ruling, the culmination of a three-year probe, saying the antitrust watchdog underestimated the competition it faced and undermined Europe-wide privacy rules that took effect last year. The findings follow fierce global scrutiny of Facebook over a series of privacy lapses, including the leak of data on tens of millions of users, as well as the extensive use of targeted ads by foreign powers seeking to influence elections in the United States. These have gone down badly with Germans, reflecting broader concerns over personal surveillance that dates back to Germany's history of Nazi and Communist rule in the 20th century.

Germany is known for its no-nonsense approach to digital data gathering -- back in 2016 it took a hard stance against Facebook's use of WhatsApp data, and more recently announced its plans to investigate the Google data exposure. Now, its anti-trust watchdog Bundeskartellamt has ordered a crackdown on Facebook's data combination practices in a landmark ruling that could have wide-ranging repercussions for the social network. As it currently stands, Facebook users are only able to use to platform under the condition that Facebook can also collect their user data outside of the network. This data comes from the company's own services, such as WhatsApp and Instagram, and from third-party websites with embedded Facebook like and share buttons -- and even on pages where there's no obvious sign the company is present. The Bundeskartellamt claims that this adds up to an abuse of market dominance, and in its ruling stipulates that Facebook may continue to collect this data only if users give their voluntary consent.

Facebook can't mix up WhatsApp and Instagram data with its own unless people consent to it, Germany has said. It has also been told to stop taking data from third-party apps and combining that with its own. Facebook collects information from across the internet – including third-party sources as well as its own other apps – and attaches it to users' accounts, in an attempt to build a more accurate picture about them and sell ads. That practise has come under intense criticism, from privacy campaigners and users who argue that it amounts to Facebook following them around the internet without their consent or event knowledge. The company has abused its market dominance to combine user data from a range of different sources, according to the German cartel office, the Bundeskartellamt.

As part of complying with the GDPR, Facebook said it had rebuilt the information its provides people about their privacy and the controls they have over their information, and improved the privacy'choices' that they are offered. It would also soon launch a'clear history' feature.

On the one hand there is a service provided to users free of charge,