Facebook has revealed 30m accounts were affected in a data breach last month. The company said hackers were able to access personal information for nearly half of those accounts. That information included name, relationship status, religion, birthdate, workplaces, search activity, and recent location check-ins. The company had initially said 50m accounts were affected. According to Facebook VP of Product Management Guy Rosen, attackers were able to access name and contact information for half of the hacked accounts.

Today, Facebook provided additional information on the data breach it disclosed last month. Whereas it initially said up to 50 million users might have been affected, it now reports that 30 million were impacted by the breach. By exploiting a system vulnerability, attackers were able to steal digital keys called access tokens from those 30 million users, and Facebook has now laid out how those users were affected. The company is also notifying those impacted, but if you don't want to wait to be notified, you can check if your account was affected through this link. The 30 million users whose access tokens were stolen fall into one of three categories.

In "How to Make a Racist AI Without Really Trying," Robyn Speer shows how to build a simple sentiment analysis system, using standard, well-known sources for word embeddings (GloVe and word2vec), and a widely used sentiment lexicon. Her program assigns "negative" sentiment to names and phrases associated with minorities, and "positive" sentiment to names and phrases associated with Europeans. Even a sentence like "Let's go get Mexican food" gets a much lower sentiment score than "Let's go get Italian food." That result isn't surprising, nor are Speer's conclusions: if you take a simplistic approach to sentiment analysis, you shouldn't be surprised when you get a program that embodies racist, discriminatory values. It's possible to minimize algorithmic racism (though possibly not eliminate it entirely), and Speer discusses several strategies for doing so.

The Irish Data Protection Commission has formally begun an investigation into Facebook's recent data breach. It will now decide whether the firm should be fined for failing to prevent hackers from being able to access up to 50 million users' accounts. Earlier this year, the social network picked the regulator to be its "one-stop shop" for oversight of its compliance with EU privacy rules. In theory, the watchdog can fine the US firm up to 4% of its global turnover. Earlier, Facebook had declared that third-party apps and services which let users log in using their accounts had not appeared to have been compromised in the security attack.

Marketers have plenty of ways to measure video campaign success, but artificial intelligence is uncovering new methods for determining whether the dollars you're spending are being applied optimally. That's what video insights company YouFirst is offering, and a recent study of one of its clients, spanning 13 video campaigns over two years, is revealing. Even with the latest and greatest analytics tools at the brand's disposal, AI and emotion tracking are opening up new insights. More importantly, AI is showing where to make changes to a campaign so it hits its exact target market -- and when to pull the plug. YouFirst works by allowing a focus group of video viewers access to the content through its player, which -- with permission -- monitors the facial expressions of the consumer via a webcam.

First, a couple of pointers to keep in mind when searching for datasets. Kaggle: A data science site that contains a variety of externally contributed interesting datasets. You can find all kinds of niche datasets in its master list, from ramen ratings to basketball data to and even seattle pet licenses. Although the data sets are user-contributed, and thus have varying levels of cleanliness, the vast majority are clean. This site makes it possible to download data from multiple US government agencies.

Text analytics based on supervised machine learning classifiers has shown great promise in a multitude of domains, but has yet to be applied to Seismology. We test various standard models (Naive Bayes, k-Nearest Neighbors, Support Vector Machines, and Random Forests) on a seismological corpus of 100 articles related to the topic of precursory accelerating seismicity, spanning from 1988 to 2010. This corpus was labelled in Mignan (2011) with the precursor whether explained by critical processes (i.e., cascade triggering) or by other processes (such as signature of main fault loading). We investigate rather the classification process can be automatized to help analyze larger corpora in order to better understand trends in earthquake predictability research. We find that the Naive Bayes model performs best, in agreement with the machine learning literature for the case of small datasets, with cross-validation accuracies of 86% for binary classification. For a refined multiclass classification ('non-critical process' < 'agnostic' < 'critical process assumed' < 'critical process demonstrated'), we obtain up to 78% accuracy. Prediction on a dozen of articles published since 2011 shows however a weak generalization with a F1-score of 60%, only slightly better than a random classifier, which can be explained by a change of authorship and use of different terminologies. Yet, the model shows F1-scores greater than 80% for the two multiclass extremes ('non-critical process' versus 'critical process demonstrated') while it falls to random classifier results (around 25%) for papers labelled 'agnostic' or 'critical process assumed'. Those results are encouraging in view of the small size of the corpus and of the high degree of abstraction of the labelling. Domain knowledge engineering remains essential but can be made transparent by an investigation of Naive Bayes keyword posterior probabilities.

LONDON – Ireland's data regulator has launched an investigation of Facebook over a recent data breach that allowed hackers access to 50 million accounts. The probe could potentially cost Facebook more than $1.6 billion in fines. The Irish Data Protection Commission said Wednesday that it will look into whether the U.S. social media company complied with European regulations that went into effect earlier this year covering data protection. It's the latest headache for Facebook in Europe, where authorities are turning up the heat on dominant tech firms over data protection. Last month, European Union consumer protection chief Vera Jourova said that she was growing impatient with Facebook for being too slow in clarifying the fine print in its terms of service covering what happens to user data and warned that the company could face sanctions.

Ireland's data regulator has launched an investigation of Facebook over a recent data breach that allowed hackers access to 50 million accounts. The probe could potentially cost Facebook more than $1.6 billion in fines. The Irish Data Protection Commission said Wednesday that it will look into whether the U.S. social media company complied with European regulations that went into effect earlier this year covering data protection. It's the latest headache for Facebook in Europe, where authorities are turning up the heat on dominant tech firms over data protection. Last month, European Union consumer protection chief Vera Jourova said that she was growing impatient with Facebook for being too slow in clarifying the fine print in its terms of service covering what happens to user data and warned that the company could face sanctions.

The Irish Data Protection Commission has opened a formal investigation into a data breach that affected nearly 50m Facebook accounts, which could result in a fine of up to $1.63bn. The breach, which was discovered by Facebook engineers on Tuesday 24 September, gave hackers the ability to take over users' accounts. It was patched on Thursday, the company said. "The investigation will examine Facebook's compliance with its obligation under the General Data Protection Regulation (GDPR) to implement appropriate technical and organisational measures to ensure the security and safeguarding of the personal data it processes," the commission said in a statement on Wednesday. The commission regulates Facebook's adherence to GDPR, a European law that strengthens the privacy protections of individuals and introduces harsh penalties for companies that fail to protect user data.