Big data approach for sentiment analysis of twitter data using Hadoop framework and deep learning

Khan, Mudassir; Malviya, Aadarsh

doi:10.1109/ic-etite47903.2020.201

Cited by 49 publications

(22 citation statements)

References 12 publications

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“…Due to the current technological requirements of big data, the company has various indicators in terms of economic information. erefore, in order to ensure that the company organizes and analyzes economic information in a timely and accurate manner, a real-time dynamic forecasting system must be designed [15]. First of all, it is required to divide the data of economic information according to the developed classification system and make clear the actual role and meaning of each economic data.…”

Section: System Designmentioning

confidence: 99%

[Retracted] Design of Enterprise Economic Information Management System Based on Big Data Integration Algorithm

Liu

2022

Journal of Mathematics

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In economic growth, the gradual increase in the effect of information technology makes the enterprise economic information management increasingly important for the survival and development of the enterprises. This paper designs an enterprise economic information management system for the complex internal economic information management business and process of enterprises. It provides daily office, information access, document preview, and transmission. The proposed design (i) copes with the inconsistency and irregularity of enterprise economic information data, (ii) quickly obtains valuable information from these massive high-frequency data, and (iii) improves the economic benefits of data assets and data management efficiency. The printing function systematizes the information management for departments such as enterprise economic information, personnel, and production. The main focus of this research includes the mode, framework, and function of the whole system software. Moreover, it also comprises of the use of Internet platform big data technology to realize the practicality, stability, and security of the system database algorithm, which has been practically used by enterprises to improve office efficiency and meet the needs of daily management of enterprises. Based on the analysis of the current status of enterprise big data application, this paper constructs an enterprise economic informational management system based on big data and also describes in detail the key technologies of enterprise economic informational data management from three aspects: NoSQL-based big data storage management, Hadoop-based economic informational big data informational and economic informational big data analysis, and mining algorithm. Provide theoretical basis and basic technical support for online decision analysis.

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Section: System Designmentioning

confidence: 99%

[Retracted] Design of Enterprise Economic Information Management System Based on Big Data Integration Algorithm

Liu

2022

Journal of Mathematics

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“…Also used significantly as a classification algorithm for sentiment analysis, Support Vector Machine classifies by finding the hyper-plane which separates classes. [4] propose an approach to sentiment analysis of twitter This approach determined the Naïve Bayes classifier to be similar in accuracy with the other classifiers, but the most precise method of classification. Dhawan et al [6] state the categorization of Artificial Intelligence (AI) me-thods for grouping data into classes, unsupervised learning, and supervised learning.…”

Section: Related Work On Sentiment Analysismentioning

confidence: 99%

Sentiment Analysis on Twitter Data Using Term Frequency-Inverse Document Frequency

Addiga¹,

Bagui²

2022

JCC

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This study is an exploratory analysis of applying natural language processing techniques such as Term Frequency-Inverse Document Frequency and Sentiment Analysis on Twitter data. The uniqueness of this work is established by determining the overall sentiment of a politician's tweets based on TF-IDF values of terms used in their published tweets. By calculating the TF-IDF value of terms from the corpus, this work displays the correlation between TF-IDF score and polarity. The results of this work show that calculating the TF-IDF score of the corpus allows for a more accurate representation of the overall polarity since terms are given a weight based on their uniqueness and relevance rather than just the frequency at which they appear in the corpus.

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“…In [3], describes the different social media and big data analytics techniques to analyse an iterative procedure of clustering method by using K-means clustering algorithm. Khan, M discussed the different era of big data using different methods and techniques [4][5] and Khan, M. and M. D. Ansari (2019) discussed the security and privacy issues in the present system [6].…”

Section: Related Workmentioning

confidence: 99%

Big Data Analytics to Authenticate Bank Notes Using K-Means Clustering

Khan¹,

Alam²

2021

helix

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The main objective of this work is to use the given dataset (about the information of different variables of the different kind of bank notes that were analyzed) in such a way using an algorithm that will group the large values in the data as efficiently as possible into two groups of values then we can use those groups and make a model that can in future identify a forged note from the real ones. Forged banknotes are a major problem that the bank must tackle. It is very important to find a solution to stop this criminal action. One of the most important steps is to be able to identify which banknote is forged. There are many solutions to identify the forged banknote. In this manuscript, we propose one of the solutions to identify the forged banknotes using one of the machine learning methods called "K-Means Clustering".

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Big data approach for sentiment analysis of twitter data using Hadoop framework and deep learning

Cited by 49 publications

References 12 publications

[Retracted] Design of Enterprise Economic Information Management System Based on Big Data Integration Algorithm

[Retracted] Design of Enterprise Economic Information Management System Based on Big Data Integration Algorithm

Sentiment Analysis on Twitter Data Using Term Frequency-Inverse Document Frequency

Big Data Analytics to Authenticate Bank Notes Using K-Means Clustering

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