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    <titleInfo>
        <title>Analysing Market Sentiments: Utilising Deep Learning to Exploit Relationships within the Economy</title>
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    <name type="personal">
        <namePart type="given">Tobias</namePart>
        <namePart type="family">Daudert</namePart>
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            <title>Proceedings of the Student Research Workshop Associated with RANLP 2017</title>
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        <name type="personal">
            <namePart type="given">Venelin</namePart>
            <namePart type="family">Kovatchev</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Irina</namePart>
            <namePart type="family">Temnikova</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Pepa</namePart>
            <namePart type="family">Gencheva</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Yasen</namePart>
            <namePart type="family">Kiprov</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Ivelina</namePart>
            <namePart type="family">Nikolova</namePart>
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    <abstract>In today’s world, globalisation is not only affecting inter-culturalism but also linking markets across the globe. Given that all markets are affecting each other and are not only driven by fundamental data but also by sentiments, sentiment analysis regarding the markets becomes a tool to predict, anticipate, and milden future economic crises such as the one we faced in 2008. In this paper, an approach to improve sentiment analysis by exploiting relationships among different kinds of sentiment, together with supplementary information, from and across various data sources is proposed.</abstract>
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    <identifier type="doi">10.26615/issn.1314-9156.2017_002</identifier>
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        <date>2017-09</date>
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%0 Conference Proceedings
%T Analysing Market Sentiments: Utilising Deep Learning to Exploit Relationships within the Economy
%A Daudert, Tobias
%Y Kovatchev, Venelin
%Y Temnikova, Irina
%Y Gencheva, Pepa
%Y Kiprov, Yasen
%Y Nikolova, Ivelina
%S Proceedings of the Student Research Workshop Associated with RANLP 2017
%D 2017
%8 September
%I INCOMA Ltd.
%C Varna
%F daudert-2017-analysing
%X In today’s world, globalisation is not only affecting inter-culturalism but also linking markets across the globe. Given that all markets are affecting each other and are not only driven by fundamental data but also by sentiments, sentiment analysis regarding the markets becomes a tool to predict, anticipate, and milden future economic crises such as the one we faced in 2008. In this paper, an approach to improve sentiment analysis by exploiting relationships among different kinds of sentiment, together with supplementary information, from and across various data sources is proposed.
%R 10.26615/issn.1314-9156.2017_002
%U https://doi.org/10.26615/issn.1314-9156.2017_002
%P 10-16

Markdown (Informal)

[Analysing Market Sentiments: Utilising Deep Learning to Exploit Relationships within the Economy](https://doi.org/10.26615/issn.1314-9156.2017_002) (Daudert, RANLP 2017)

• Analysing Market Sentiments: Utilising Deep Learning to Exploit Relationships within the Economy (Daudert, RANLP 2017)

ACL

• Tobias Daudert. 2017. Analysing Market Sentiments: Utilising Deep Learning to Exploit Relationships within the Economy. In Proceedings of the Student Research Workshop Associated with RANLP 2017, pages 10–16, Varna. INCOMA Ltd..