The European Union says that Facebook has told it that up to 2.7 million people in the 28-nation bloc may have been victim of improper data sharing involving political data-mining firm Cambridge Analytica. Now the EU says that it will ask the data protection authorities in its various countries to work together and investigate the site for the abuse of data. As the data sharing scandal has spread, estimates of the number of people caught up in it have increased. This week, Facebook said that at least 87 million people across the world had been affected by it. Many of those people are outside of Europe.

WASHINGTON – Investigators on two congressional panels are looking into whether Russia acquired the data of millions of Facebook users and if companies with ties to then-2016 Republican election candidate Donald Trump's campaign played any role in providing it, three sources familiar with the inquiries said. On Tuesday, Facebook said it had deleted 70 Facebook accounts, 138 Facebook pages and 65 Instagram accounts that it said were "controlled" by the Internet Research Agency (IRA), a Russian propaganda arm based in St. Petersburg. Last September, Facebook disclosed that it had suspended about 470 "inauthentic accounts" that it believed were "likely operated out of Russia" and had purchased 3,000 ads which "appeared to focus on amplifying divisive social and political messages." And on Wednesday, the social media platform said the personal information of up to 87 million users, mostly in the United States, may have been improperly shared with political consultancy Cambridge Analytica, up from a previous news media estimate of more than 50 million. Chief Executive Officer Mark Zuckerberg will testify on April 10 and 11 to Congress.

Understanding a customer’s personal opinion is extremely important to initiate and maintain a meaningful conversation. In this paper, we propose an approach to extract latent emotional beliefs of customers and use them to tailor a chatbot’s conversation. We present a machine learning based mechanism to process customer complaints and extract sentiments like customer is sad, happy, upset, etc. Further, we also train a model that extract more fine grain sentiments like the customer is irritated, harassed etc. in context of a particular complaint scenario. This information helps to tailor the dialog according to customer’s emotional state and hence improve the overall effectiveness of the dialog system.

Among the issues investigators on the U.S. Senate Intelligence Committee and Democrats on the House Intelligence Committee are digging into are whether IRA and other Russian organizations used any Facebook data, the sources said, speaking on condition of anonymity. Also, whether the use of such data had any impact on the U.S. election, and how much Facebook data may have been acquired by Russian entities, the sources said.

Facebook CEO Mark Zuckerberg will appear before the US House Commerce Committee on 11 April to explain his company's part in the Cambridge Analytica data breach scandal. The hearing will be broadcast on C-SPAN and be available to stream online on the channel's website. The story broke on 17 March that Cambridge Analytica, a "strategic communications" consultancy, had harvested information from the profiles of 50m Facebook users - now thought to be closer to 87m - and sold it on to the Donald Trump campaign for use in the micro-targeting of swing voters in the run-up to the 2016 US presidential election. The Vote Leave campaign pushing for Britain to quit the European Union are also understood to have employed the company's services prior to the Brexit referendum in 2016. Cambridge Analytica had acquired the data from Global Science Research (GSR), a firm run by academic Dr Aleksandr Kogan, who had been carrying out a personality test using a third-party app called This is Your Digital Life that required its 270,000 paid participants to provide access to their Facebook pages.

Australian authorities say they are investigating whether Facebook breached the country's privacy law when personal information of more than 300,000 Australian users was obtained by Cambridge Analytica, a Trump-linked political consulting firm, without their authorization.

On the same day that Facebook announced that 87 million users may have had their personal data improperly accessed -- updated from the "tens of millions" figure the social network previously reported -- the company's founder and CEO Mark Zuckerberg held a rare question-and-answer session with the media Wednesday, admitting that the company made a "huge mistake" by not taking more steps to protect user data and privacy early on. When asked if he thinks he is still the best person to run Facebook, Zuckerberg said, "Yes, I think life is about learning from the mistakes and figuring out what you need to do to move forward." Questions about Zuckerberg's leadership come after it's been revealed that Cambridge Analytica might have improperly obtained data from as many as 87 million people, mostly in the United States. The firm had ties to President Donald Trump's 2016 campaign. "At the end of the day, this is my responsibility," Zuckerberg said, when asked if anyone at Facebook had been fired over the Cambridge Analytica scandal.

The ability to identify sentiment in text, referred to as sentiment analysis, is one which is natural to adult humans. This task is, however, not one which a computer can perform by default. Identifying sentiments in an automated, algorithmic manner will be a useful capability for business and research in their search to understand what consumers think about their products or services and to understand human sociology. Here we propose two new Genetic Algorithms (GAs) for the task of automated text sentiment analysis. The GAs learn whether words occurring in a text corpus are either sentiment or amplifier words, and their corresponding magnitude. Sentiment words, such as 'horrible', add linearly to the final sentiment. Amplifier words in contrast, which are typically adjectives/adverbs like 'very', multiply the sentiment of the following word. This increases, decreases or negates the sentiment of the following word. The sentiment of the full text is then the sum of these terms. This approach grows both a sentiment and amplifier dictionary which can be reused for other purposes and fed into other machine learning algorithms. We report the results of multiple experiments conducted on large Amazon data sets. The results reveal that our proposed approach was able to outperform several public and/or commercial sentiment analysis algorithms.

INFORMATION wants to be free. This decades-old slogan is the philosophical heart of the internet, putting nearly all human knowledge at our fingertips, free to anyone with a connection. Here is another old slogan: if you're not paying, you're the product. We might not hand over cash for many of the services we get from the internet giants, but we do pay in cold, hard data. On the whole, we have been happy to make that pact.

Future Tense is a partnership of Slate, New America, and Arizona State University that examines emerging technologies, public policy, and society. Facebook disclosed in a blog post on Wednesday that political consulting firm Cambridge Analytica accessed the private data of a considerably larger number of people than was previously known. "In total, we believe the Facebook information of up to 87 million people--mostly in the US--may have been improperly shared with Cambridge Analytica," he wrote. The New York Times and other outlets have been reporting that about 50 million people were affected based on information from whistleblower Christopher Wylie, who formerly worked at Cambridge Analytica. Facebook CEO Mark Zuckerberg clarified later in a press call that 87 million was the maximum number of accounts that Cambridge Analytica could have accessed, though the actual number is probably lower.