{"title":"Leveraging time for spammers detection on Twitter","authors":"Mahdi Washha, Aziz Qaroush, F. Sèdes","doi":"10.1145/3012071.3012078","DOIUrl":"https://doi.org/10.1145/3012071.3012078","url":null,"abstract":"Twitter is one of the most popular microblogging social systems, which provides a set of distinctive posting services operating in real time. The flexibility of these services has attracted unethical individuals, so-called \"spammers\", aiming at spreading malicious, phishing, and misleading information. Unfortunately, the existence of spam results non-ignorable problems related to search and user's privacy. In the battle of fighting spam, various detection methods have been designed, which work by automating the detection process using the \"features\" concept combined with machine learning methods. However, the existing features are not effective enough to adapt spammers' tactics due to the ease of manipulation in the features. Also, the graph features are not suitable for Twitter based applications, though the high performance obtainable when applying such features. In this paper, beyond the simple statistical features such as number of hashtags and number of URLs, we examine the time property through advancing the design of some features used in the literature, and proposing new time based features. The new design of features is divided between robust advanced statistical features incorporating explicitly the time attribute, and behavioral features identifying any posting behavior pattern. The experimental results show that the new form of features is able to classify correctly the majority of spammers with an accuracy higher than 93% when using Random Forest learning algorithm, applied on a collected and annotated data-set. The results obtained outperform the accuracy of the state of the art features by about 6%, proving the significance of leveraging time in detecting spam accounts.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"208 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133353835","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}
{"title":"A semantic-web-technology-based framework for supporting knowledge-driven digital forensics","authors":"A. Cuzzocrea, G. Pirrò","doi":"10.1145/3012071.3012099","DOIUrl":"https://doi.org/10.1145/3012071.3012099","url":null,"abstract":"The usage of Information and Communication Technologies (ICTs) pervades everyday's life. If it is true that ICT contributed to improve the quality of our life, it is also true that new forms of (cyber)crime have emerged in this setting. The diversity and amount of information forensic investigators need to cope with, when tackling a cyber-crime case, call for tools and techniques where knowledge is the main actor. Current approaches leave to the investigator the chore of integrating the diverse sources of evidence relevant for a case thus hindering the automatic generation of reusable knowledge. This paper describes an architecture that lifts the classical phases of a digital forensic investigation to a knowledge-driven setting. We discuss how the usage of languages and technologies originating from the Semantic Web proposal can complement digital forensics tools so that knowledge becomes a first-class citizen. Our architecture enables to perform in an integrated way complex forensic investigations and, as a by-product, build a knowledge base that can be consulted to gain insights from previous cases. Our proposal has been inspired by real-world scenarios emerging in the context of an Italian research project about cyber security.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115771587","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}
{"title":"Ranking solar energy potential by class and country","authors":"Michael Kommeh, R. Agrawal, Adeyinka Olurin","doi":"10.1145/3012071.3012091","DOIUrl":"https://doi.org/10.1145/3012071.3012091","url":null,"abstract":"The global ecosystem has been adversely affected by our over reliance on fossil fuels, nuclear energy and other forms which are less environmentally friendly. Of course, this is not the only reason for which advances are made into finding alternative sources of energy; rising fossil fuel prices, the expense of installing and managing nuclear plants and industrial emissions naturally force the hand of developed and developing countries to look into various ways of producing cleaner and safer forms of energy albeit however little. The energy from the sun is enough to take care of global energy needs at any given time thus presenting solar energy as our most efficient, unlimited and affordable form of renewable energy. Therefore, creating an index of global countries based on the amount of solar energy they receive throughout the year gives an informed perspective on how we can further maximize this resource. This paper ranks solar resources by class and country based on statistical data to show the solar potential of countries globally. With the decline in solar cost, solar energy has become the supplemental option among renewable forms of energy. This is essential as it shows which countries across the globe have solar resources in large quantities and whose benefits can be exploited through funding and investments.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123953520","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}
{"title":"Sentiment analysis from textual to multimodal features in digital environments","authors":"M. Caschera, F. Ferri, P. Grifoni","doi":"10.1145/3012071.3012089","DOIUrl":"https://doi.org/10.1145/3012071.3012089","url":null,"abstract":"When social networks actors are involved in the production, consumption and exchange of content and information by texts, images, audios, videos, they act in a shared digital environment that can be considered as a digital ecosystem. On the increasing size of produced data, an open issue is the understanding of the real sentiment and emotion from texts, but also from images, audios and videos. This issue is particularly relevant for monitoring and identifying critical situations and suspicious behaviours. This paper is an attempt to review and evaluate the various techniques used for sentiment and emotion analysis from text, audio and video, and to discuss the main challenges addressed in extracting sentiment from multimodal data. The paper concludes the discussion by proposing a method that combines a machine learning approach with a language-based formalization in order to extract sentiment from multimodal data formalized through a multimodal language.","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121910626","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}
{"title":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","authors":"R. Chbeir, R. Agrawal, Ismaïl Biskri","doi":"10.1145/3012071","DOIUrl":"https://doi.org/10.1145/3012071","url":null,"abstract":"","PeriodicalId":294250,"journal":{"name":"Proceedings of the 8th International Conference on Management of Digital EcoSystems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114156131","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}