SSIX - Social Sentiment Indices powered by X-Scores

23/06/16 09:00 – 14:00 CET   The average Brexit opinion remains stable on the ‘Remain’ side, as identified during the last days. The volume of the ‘Remain’ tweets is slightly bigger than ‘Leave’. Per minute there are more tweets for ‘Remain’ than for ‘Leave’. Volatility of the signal remains low and stable.   The vote… » read more

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The Twitter sentiment analysis indicates that ‘Remain’ is still on course to a victory but is getting weaker. In general the win side will most likely have a marginal victory, as ‘Remain/Leave’ vote is going to be very tight. The monitoring performed by the SSIX consortium shows a weakening pattern over the last 72h for… » read more

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A slight weakening in the ‘Remain’ side can be noticed. ‘Remain’ opinion is still within the positive range, showing small volatility but a slightly downward trend, while ‘Leave’ opinion is gaining some momentum. Overall the monitoring performed shows us a side-ways/ horizontal ‘Remain’ trend as preference of Twitter users. Percentage share of Tweets: 59.9% ‘Remain’… » read more

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This is the conclusion of the Brexit monitoring from today (21 June) by the SSIX EU project consortium. All the X-scores show us that there is a stable trend with low volatility within the Twitter opinion towards staying in the EU. The X-scores provide us with the ability to understand sentiment/opinion behaviour in detail and… » read more

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The social sentiment monitoring of the upcoming Brexit vote is our very first attempt to test the SSIX technology live. Originally, we had not envisioned that politics would be its very first real world test. However, Brexit is a unique event not to be missed, due to its global economic impact, as well as political… » read more

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Following the activities initiated last September in Budapest, this whole week the SSIX Project will be in Vancouver (BC, Canada) for attending the ApacheCon North America 2016. ApacheCon is a well-established event in the open source community. For more than a decade, these events have brought the Apache project community together to meet, network, learn… » read more

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Why Machine Learning? Can computers learn how to perform complex tasks such as driving autonomous cars [1], spotting cancer cells [2] or analysing sentiment [3] without being specifically instructed? The answer is Yes – and Machine Learning (ML) provides the tools! Rather than relying on explicit instructions (rules), ML systems learn from examples. This allows… » read more

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As discussed in a previous post, Social Network data will be one of the main sources of the SSIX Sentiment Analysis platform for Financial domains. It is well known that the amount of data made available from such sources is huge, and the first challenge is to be able to filter relevant content out of… » read more

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Twitter is one of the platforms identified as data source within the SSIX project. Let’s see the different techniques that can be used to retrieve this data and the difficulties that derive from them. SSIX decided to adopt Twitter as a primary source of information used to spot financial trends and to calculate the indices… » read more

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Policymakers are showing growing interest for real-time analysis of public opinion and Big Data. From finance to political campaigners, social media have become a primary source of information, especially when it comes to understanding public opinion trends.     However, the potential of social media still needs to be fully exploited. With the explosion of… » read more

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