Pub Date : 2019-10-01DOI: 10.1109/ICSSD47982.2019.9002981
Hind Bourezk, Amine Raji, Nawfal Acha, Hafid Barka
A growing body of research and practical applications employ social media data as a proxy for the complex behavior of investors in financial markets. This paper provides an overview of academic research related to the link between social media and financial markets in order to give insight into future works and challenges on investor sentiment analysis. The theoretical rationale of this relationship is predominantly defined by behavioral finance. Behavioral finance shows that emotions have a considerable impact on individual behavior. Researchers of this discipline contradict the standard model of efficient markets and considers irrational factors like investors sentiment and public mood as influential for asset pricing and financial market volatility. In this context, social media is a novel tool enabling the collection of data about such behavioral factors.
{"title":"An Overview on Sentiment Mining for Stock Market prediction","authors":"Hind Bourezk, Amine Raji, Nawfal Acha, Hafid Barka","doi":"10.1109/ICSSD47982.2019.9002981","DOIUrl":"https://doi.org/10.1109/ICSSD47982.2019.9002981","url":null,"abstract":"A growing body of research and practical applications employ social media data as a proxy for the complex behavior of investors in financial markets. This paper provides an overview of academic research related to the link between social media and financial markets in order to give insight into future works and challenges on investor sentiment analysis. The theoretical rationale of this relationship is predominantly defined by behavioral finance. Behavioral finance shows that emotions have a considerable impact on individual behavior. Researchers of this discipline contradict the standard model of efficient markets and considers irrational factors like investors sentiment and public mood as influential for asset pricing and financial market volatility. In this context, social media is a novel tool enabling the collection of data about such behavioral factors.","PeriodicalId":342806,"journal":{"name":"2019 1st International Conference on Smart Systems and Data Science (ICSSD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129145479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ICSSD47982.2019.9003030
Lamia Moudoubah, Abir El Yamami, K. Mansouri, Mohammed Qbadou
for most organizations, understanding the contribution of IT infrastructure to achieve desired objectives is very important. In this context, the IT governance framework COBIT (Control Objective for Information and related Technology) includes a set of essential tools to ensure the monitoring and the control of IT governance. However, COBIT does not provide machine-readable data. Hence, the objective of this paper is to develop an ontology based on COBIT V5 framework called “CobitOntology”. “CobitOntology” is an IT governance solution that will clarify the domain vocabulary and the dependencies between the different elements of the domain. This ontology is realized from text, i. e. from the use of text corpuses, extracting terms and relationships between these terms to make an ontology. We will therefore use a linguistic analysis using a statistical analysis of a corpus (term frequency and inverse document frequency).
{"title":"Towards the implementation of an ontology based on COBIT framework (CobitOnyology)","authors":"Lamia Moudoubah, Abir El Yamami, K. Mansouri, Mohammed Qbadou","doi":"10.1109/ICSSD47982.2019.9003030","DOIUrl":"https://doi.org/10.1109/ICSSD47982.2019.9003030","url":null,"abstract":"for most organizations, understanding the contribution of IT infrastructure to achieve desired objectives is very important. In this context, the IT governance framework COBIT (Control Objective for Information and related Technology) includes a set of essential tools to ensure the monitoring and the control of IT governance. However, COBIT does not provide machine-readable data. Hence, the objective of this paper is to develop an ontology based on COBIT V5 framework called “CobitOntology”. “CobitOntology” is an IT governance solution that will clarify the domain vocabulary and the dependencies between the different elements of the domain. This ontology is realized from text, i. e. from the use of text corpuses, extracting terms and relationships between these terms to make an ontology. We will therefore use a linguistic analysis using a statistical analysis of a corpus (term frequency and inverse document frequency).","PeriodicalId":342806,"journal":{"name":"2019 1st International Conference on Smart Systems and Data Science (ICSSD)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121977051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ICSSD47982.2019.9002836
Nahir Abir, Aalaoui Zinab, T. Mourad
Nowadays, we see almost of people talk about industry 4.0, but no one has a clear information exactly about this term. As we now the industry across many years saw a very important improvement. In this study we will look up the definition of industry 4.0, the comparison between four countries that compete about industry 4.0 in which each country has its own term about the fourth revolution industry that really will change our lives completely with the introduction of the internet. The countries that we will see are China with its proper term ‘made in China 2025’ or ‘internet +’ then France with its name ‘new France industrial’ (NFI) and the leader Germany with ‘industry 4.0’ also don’t forget the United States with its own terms ‘advancing manufacturing program’ or ‘industrial internet’, many other countries have its own term. Then, we are focusing in these four countries because they are the most working in this field. So, in this study we will define industry 4.0 and compare the countries and their works about the fourth revolution industrial.
{"title":"Industry 4.0 plans","authors":"Nahir Abir, Aalaoui Zinab, T. Mourad","doi":"10.1109/ICSSD47982.2019.9002836","DOIUrl":"https://doi.org/10.1109/ICSSD47982.2019.9002836","url":null,"abstract":"Nowadays, we see almost of people talk about industry 4.0, but no one has a clear information exactly about this term. As we now the industry across many years saw a very important improvement. In this study we will look up the definition of industry 4.0, the comparison between four countries that compete about industry 4.0 in which each country has its own term about the fourth revolution industry that really will change our lives completely with the introduction of the internet. The countries that we will see are China with its proper term ‘made in China 2025’ or ‘internet +’ then France with its name ‘new France industrial’ (NFI) and the leader Germany with ‘industry 4.0’ also don’t forget the United States with its own terms ‘advancing manufacturing program’ or ‘industrial internet’, many other countries have its own term. Then, we are focusing in these four countries because they are the most working in this field. So, in this study we will define industry 4.0 and compare the countries and their works about the fourth revolution industrial.","PeriodicalId":342806,"journal":{"name":"2019 1st International Conference on Smart Systems and Data Science (ICSSD)","volume":"73 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132433180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ICSSD47982.2019.9002823
Yasmine Lahlou, Sanaa El Fkihi, R. Faizi
In recent years, a lot of fake news are generated on the web in order to attract readership, influence opinions, and increase internet click revenue. The generation of this false information has become a worldwide phenomenon and its effects are notorious as it leads to confusion over facts and causes wrong decision-making.However, evaluating and detecting the veracity of news can be a complex and cumbersome task. This is simply because most of the studies carried out so far on the detection of such news, especially in real time, are not really performant.. Our objective in this work is, therefore, to review the major works that have addressed this problem. Results of this study have revealed that two major approaches have been put forward, namely linguistic and network. In this article, we will try to quote a set of automatic detection of false news on the web and social networks.
{"title":"Automatic detection of fake news on online platforms: A survey","authors":"Yasmine Lahlou, Sanaa El Fkihi, R. Faizi","doi":"10.1109/ICSSD47982.2019.9002823","DOIUrl":"https://doi.org/10.1109/ICSSD47982.2019.9002823","url":null,"abstract":"In recent years, a lot of fake news are generated on the web in order to attract readership, influence opinions, and increase internet click revenue. The generation of this false information has become a worldwide phenomenon and its effects are notorious as it leads to confusion over facts and causes wrong decision-making.However, evaluating and detecting the veracity of news can be a complex and cumbersome task. This is simply because most of the studies carried out so far on the detection of such news, especially in real time, are not really performant.. Our objective in this work is, therefore, to review the major works that have addressed this problem. Results of this study have revealed that two major approaches have been put forward, namely linguistic and network. In this article, we will try to quote a set of automatic detection of false news on the web and social networks.","PeriodicalId":342806,"journal":{"name":"2019 1st International Conference on Smart Systems and Data Science (ICSSD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125896582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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