{"title":"使用云进行安全资本市场分析的预处理推文","authors":"Sangeeta Gupta, Dr Rajanikanth Aluvalu","doi":"10.4018/IJSKD.2021010101","DOIUrl":null,"url":null,"abstract":"Huge crowds heading towards smart investment options need a secure and trustworthy environment to earn good profits. Twitter, a social networking platform, is a major source generating huge information on share market consortium. People get excited when they come across the tweets that specify the shares yielding huge profits within a short time. Due to this, they end up tweeting about their credentials and amount they are willing to invest. It paves a path for the intruders to access confidential data and leave the common man in danger by gaining access and misusing the information. Towards this end, the goal of this work is to address the challenge of providing better inputs to the customers interested to invest in the share market in a secure way to earn better returns on investment. In this work, as a first module, pre-processing techniques are used to remove the unwanted characters from tweets. In the second part, to enhance the security, encryption module is developed, and the data is then stored in Cassandra. It is observed from results that the time taken to encrypt 100,000 tweets after pre-processing is 500 msec, and the time taken to decrypt the same set of 100,000 tweets is 50 msec, respectively. This shows the effectiveness of the proposed work in terms of attaining better and fast outcomes for a huge set of tweets after filling the voids by pre-processing techniques.","PeriodicalId":13656,"journal":{"name":"Int. J. Sociotechnology Knowl. Dev.","volume":"1 1","pages":"1-7"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Pre-Processed Tweets for Secure Capital Market Analysis Using Cloud\",\"authors\":\"Sangeeta Gupta, Dr Rajanikanth Aluvalu\",\"doi\":\"10.4018/IJSKD.2021010101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Huge crowds heading towards smart investment options need a secure and trustworthy environment to earn good profits. Twitter, a social networking platform, is a major source generating huge information on share market consortium. People get excited when they come across the tweets that specify the shares yielding huge profits within a short time. Due to this, they end up tweeting about their credentials and amount they are willing to invest. It paves a path for the intruders to access confidential data and leave the common man in danger by gaining access and misusing the information. Towards this end, the goal of this work is to address the challenge of providing better inputs to the customers interested to invest in the share market in a secure way to earn better returns on investment. In this work, as a first module, pre-processing techniques are used to remove the unwanted characters from tweets. In the second part, to enhance the security, encryption module is developed, and the data is then stored in Cassandra. It is observed from results that the time taken to encrypt 100,000 tweets after pre-processing is 500 msec, and the time taken to decrypt the same set of 100,000 tweets is 50 msec, respectively. This shows the effectiveness of the proposed work in terms of attaining better and fast outcomes for a huge set of tweets after filling the voids by pre-processing techniques.\",\"PeriodicalId\":13656,\"journal\":{\"name\":\"Int. J. Sociotechnology Knowl. Dev.\",\"volume\":\"1 1\",\"pages\":\"1-7\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Sociotechnology Knowl. Dev.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/IJSKD.2021010101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Sociotechnology Knowl. Dev.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJSKD.2021010101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pre-Processed Tweets for Secure Capital Market Analysis Using Cloud
Huge crowds heading towards smart investment options need a secure and trustworthy environment to earn good profits. Twitter, a social networking platform, is a major source generating huge information on share market consortium. People get excited when they come across the tweets that specify the shares yielding huge profits within a short time. Due to this, they end up tweeting about their credentials and amount they are willing to invest. It paves a path for the intruders to access confidential data and leave the common man in danger by gaining access and misusing the information. Towards this end, the goal of this work is to address the challenge of providing better inputs to the customers interested to invest in the share market in a secure way to earn better returns on investment. In this work, as a first module, pre-processing techniques are used to remove the unwanted characters from tweets. In the second part, to enhance the security, encryption module is developed, and the data is then stored in Cassandra. It is observed from results that the time taken to encrypt 100,000 tweets after pre-processing is 500 msec, and the time taken to decrypt the same set of 100,000 tweets is 50 msec, respectively. This shows the effectiveness of the proposed work in terms of attaining better and fast outcomes for a huge set of tweets after filling the voids by pre-processing techniques.