Generating emotional language is a key step towards building empathetic natural language processing agents. However, a major challenge for this line of research is the lack of large-scale labeled training data, and previous studies are limited to only small sets of human annotated sentiment labels. Additionally, explicitly controlling the emotion and sentiment of generated text is also difficult. In this paper, we take a more radical approach: we exploit the idea of leveraging Twitter data that are naturally labeled with emojis. More specifically, we collect a large corpus of Twitter conversations that include emojis in the response, and assume the emojis convey the underlying emotions of the sentence. We then introduce a reinforced conditional variational encoder approach to train a deep generative model on these conversations, which allows us to use emojis to control the emotion of the generated text. Experimentally, we show in our quantitative and qualitative analyses that the proposed models can successfully generate high-quality abstractive conversation responses in accordance with designated emotions.

Update 23 Aug 2017: Do note that Quantopian platform will no longer support third party broker integration. Please see their website under forum. The title of the post is "Phasing Out Brokerage Integrations". This course provides you with the tools that top hedge funds used. These institutional tools include but are not limited to market data, fundamental data, sentiment analysis data, and more.

Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, he provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: processes, methods, techniques, tools, and metrics; the role and management of data; text and web mining; sentiment analysis; and Big Data integration.

Word embeddings have been widely used in sentiment classification because of their efficacy for semantic representations of words. Given reviews from different domains, some existing methods for word embeddings exploit sentiment information, but they cannot produce domain-sensitive embeddings. On the other hand, some other existing methods can generate domain-sensitive word embeddings, but they cannot distinguish words with similar contexts but opposite sentiment polarity. We propose a new method for learning domain-sensitive and sentiment-aware embeddings that simultaneously capture the information of sentiment semantics and domain sensitivity of individual words. Our method can automatically determine and produce domain-common embeddings and domain-specific embeddings. The differentiation of domain-common and domain-specific words enables the advantage of data augmentation of common semantics from multiple domains and capture the varied semantics of specific words from different domains at the same time. Experimental results show that our model provides an effective way to learn domain-sensitive and sentiment-aware word embeddings which benefit sentiment classification at both sentence level and lexicon term level.

Facebook may have succeeded in getting Cambridge Analytica to delete millions of users' data in January 2016, but the information based on that data appears to have survived for much longer. The Guardian has obtained leaked emails suggesting that Cambridge Analytica avoided explicitly agreeing to delete the derivatives of that data, such as predictive personality models. Former employees claimed the company kept that data modelling in a "hidden corner" of a server until an audit in March 2017 (prompted by an Observer journalist's investigation), and it only certified that it had scrubbed the data models in April 2017 -- half a year after the US presidential election. In a response to the Guardian, a Cambridge Analytica spokesperson denied that there was a "secret cache," and said that it had started looking for and deleting derivatives of that data after the initial wipe, finishing in April 2017. It was a "lengthy process," the company claimed.

Facebook's failure to compel Cambridge Analytica to delete all traces of data from its servers – including any "derivatives" – enabled the company to retain predictive models derived from millions of social media profiles throughout the US presidential election, the Guardian can reveal. Leaked emails reveal that when Cambridge Analytica told Facebook almost a year before the election that it had deleted data harvested from tens of millions of Facebook users, it stopped short of agreeing to also erase derivatives of the data. The correspondence, obtained by the Guardian, also raises questions about the accuracy of the testimony that Facebook's chief executive, Mark Zuckerberg, gave to the US Congress last month. Derivatives of data, which can include predictive models, or clusters of populations in psychological groupings, can be highly valuable to companies involved in micro-targeting advertisements to voters. Data scientists say such models and analysis are often more valuable than underlying raw data.

Qualitative data science sounds like a contradiction in terms. Data scientists generally solve problems using numerical solutions. Even the analysis of text is reduced to a numerical problem using Markov chains, topic analysis, sentiment analysis and other mathematical tools. Scientists and professionals consider numerical methods the gold standard of analysis. There is, however, a price to pay when relying on numbers alone.

The company decided to close its doors because it was losing clients and facing mounting legal fees in the Facebook investigation, according to people familiar with the matter. SCL Group and SCL Elections, which are affiliated with Cambridge Analytica, also are shutting down in the U.S. and the U.K. Cambridge Analytica and SCL Elections issued a joint statement on Wednesday confirming the companies' closures. "Over the past several months, Cambridge Analytica has been the subject of numerous unfounded accusations," the statement said. "The siege of media coverage has driven away virtually all of the company's customers and suppliers. As a result, it has been determined that it is no longer viable to continue operating the business."

Cambridge Analytica, the data firm at the centre of this year's Facebook privacy row, is closing and starting insolvency proceedings. The company has been plagued by scandal since the Observer reported that the personal data of about 50 million Americans and at least a million Britons had been harvested from Facebook and improperly shared with Cambridge Analytica. Cambridge Analytica denies any wrongdoing, but says that the negative media coverage has left it with no clients and mounting legal fees. "Despite Cambridge Analytica's unwavering confidence that its employees have acted ethically and lawfully, the siege of media coverage has driven away virtually all of the Company's customers and suppliers," said the company in a statement, which also revealed that SCL Elections Ltd, the UK entity affiliated with Cambridge Analytica, would also close and start insolvency proceedings. "As a result, it has been determined that it is no longer viable to continue operating the business, which left Cambridge Analytica with no realistic alternative to placing the company into administration."

Facebook's reputation took a massive hit earlier this year when it was revealed that it had improperly provided user data to UK-based political consulting firm Cambridge Analytica. However, the damage appeared to be much greater in the other direction, as the controversial Cambridge Analytica announced Wednesday that it would cease operations and file for bankruptcy. Cambridge Analytica is shutting down. The firm with ties to Trump's campaign says the Facebook data scandal drove away business. The firm announced its closure in a statement on its website.