SSIX - Social Sentiment Indices powered by X-Scores

Archives for Innovation & Enterprise

One year ago people all over the world were still trying to understand the political earthquake of the Brexit-Votum and a few months later Donald Trump was elected as US president. At that time, the journalists Hannes Grassegger and Mikael Krogerus published an article in the Swish magazine “Das Magazin”, which immediately went viral in… » read more

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Investors daily have received news and opinions about different stocks or firms through specialised platforms. These one convey information, which leads different investors to make decisions. These decisions impact the market, which aggregates the information that investors receive and reflects it via the price of the firms or stocks. Given an algorithm for classifying text… » read more

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SSIX Sentiment Analysis and Opinion Mining platform intends to monitor specific topics that are discussed in texts from several sources, including social networks, which are rich repositories of people’s opinions. While the technology that is currently being developed is open and flexible to application to various domains (i.e. politics, sport, etc.), the data filtering component… » read more

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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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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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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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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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The SSIX project was presented, by Keith Cortis from the University of Passau, at the second International Conference on Big Data, Small Data, Linked Data and Open Data (ALLDATA 2016). The conference took place in Portugal, more precisely in Lisbon on 22 February 2016. ALLDATA 2016 was one of a number of conferences organised as… » read more

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  Filtering out irrelevant data before sampling Pre-sampling filtering aims to discard the least relevant data elements. This filtering can be done by removing unwanted spam content appearing on social networks generated by spambots, an example would be to discard text data which doesn’t contain emoticons as social media robots rarely use them. An alternative… » read more

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