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Bhuvaneswari, R.
- A Survey on Various Techniques for Sentiment Analysis and Opinion Mining
Authors
1 Department of Computer Science, Research and Development Centre, Bharathiar University, Coimbatore-641046, Tamil Nadu, IN
2 Department of Computer Science, H.H. The Rajah's College, Pudukkottai-622001, Tamil Nadu, IN
3 Department of Computer Science, St. Joseph's College, Trichy-620002, IN
Source
Data Mining and Knowledge Engineering, Vol 8, No 3 (2016), Pagination: 78-82Abstract
Sentiment analysis could be a range of language process for chase the mood of the general public a few unambiguous product or topic. Sentiment analysis, which is additionally called as opinion mining, involves in building a system to gather and examine opinions regarding the merchandise created in journal posts, comments, reviews or tweets. Here in this paper various sentiment analysis techniques are reviewed. The review sites mentioned for the awareness and various author's proposals are tabulated.Keywords
Sentiment Analysis, Opinion Mining, Joint Segmentation, NLP, POS Tagging.
- A Study on Factors Involving the Usage of Social Media on Investment Decision Making with Reference to Investors of Selected Stock Broking Houses in Coimbatore
Authors
1 Department of Management, PSGR Krishnammal College for Women, Coimbatore - 641004, Tamil Nadu, IN
Source
Indian Journal of Economics and Development, Vol 7, No 1 (2019), Pagination: 1-7Abstract
Objectives: Nowadays, with the rise of social media, there is possible to get a faster, more talented way of gathering data to persuade investors’ judgements. Hence, this study is trying to analyse the factors, namely Company news, Industry performance, Market updates, Economic factors and Investor sentiment which persuading the social media usage among the equity investors in Coimbatore District, Tami Nadu, India.
Research Methods: For this study, 100 investors who invest in the share market are selected by using stratified proportionate random sampling method. Self designed questionnaire is used to collect the primary data. The collected data has been evaluated with Percentage Analysis, Weighted Average Rank Analysis, Multiple Response Analysis, Correlation Analysis and Multiple Linear Regression Analysis.
Findings/Results: Out of the five independent variables, Company News, Economic Factors and Investor Sentiment have much influenced the dependent variable Investment decision making as it is statistically significant at the 5% level. Finally, the result of the study shows that social media helps to acquire timely information and gain knowledge which helps to formulate better decision by the investors.
Conclusion/Suggestions: Stock broking firms should take appropriate steps to improve the security system of social media to make investors use it effectively. This study helps the stock broker to make the valuable communication with investors, implementation of innovative technology and to promote other financial products.
Keywords
Social Media, Share Market, Equity Investor, Investment Decision Making.Full Text
References
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- Meat Merchandising in Single Look Produce the Chance of Foodborne Illness:Shoppers Alert!
Authors
1 Bharathiar University, Coimbatore, Tamil Nadu, IN
2 Karunya Institute of Technology and Sciences (Deemed to be University), IN
3 School of Engineering Technology, Purdue University, Indiana-47907, US
Source
Indian Journal of Public Health Research & Development, Vol 10, No 12 (2019), Pagination: 444-449Abstract
Purpose: The aim of the study is to produce information of food safety relates to meat consumption to guage the knowledge and angle of shoppers to make the notice publically to avoid the chance of foodborne ill health. Here the investigation belongs to however the shoppers square measure influenced by getting at totally different levels of meat below the chance perception.
Design/methodology/approach-Structural equation modeling (SEM) was engineered to grasp the chance perception of urban and rural shoppers in Coimbatore, Erode and Nilgris by scale back with the perceived risk of their probability of goat meat, chicken, fish, beef and pork.
Findings–The intentions of shoppers in these 3 districts is to facilitate with the acquisition behavior, attitude, knowledge, food safety awareness square measure involved with the microbiological risk of food contamination.
Social implications-The retail search oversubscribed their meat and poultry in single buy their convenience of shopper to avoid wasting time period and cash by mistreatment constant knife and board. It’ll produce the microbiological risk and facilitate to grasp the food handling behavior conjointly to guage the effectiveness of food safety to avoid the chance.
Practical implication-The merchant and shopper prefers these quite consumption for saving the time and cash to urge all meat in one place however they’re not knowing the chance of pathogens they use same knife and cutting all meat and poultry this produce the chance of food borne sickness and also the snacks search, tea shop, fruit stall square measure closely around the meat search and also the meat search marketing in Associate in Nursing open show there’s a necessity of closed glass box that stop mud, and bug will unfold the sickness.
Research implications–The result offer with the data of food safety steerage from producer to shopper to avoid the chance of foodborne ill health and create safe consumption to the buyer with clean and clear setting.
Originality worth–The risks are unknown by the retailers and shoppers it provides the data of meat consumption that relates to food safety with detail understanding of risk perception.
Keywords
Food Safety, Shopper Risk, Hazards, Interference Of Cross-contamination, Correct Cleanup And Sanitizing, Shopper Education.- Analysis of Online Intrusion Detection Models to Incorporate Secured Digital Cash Transaction in Mobile Smart Systems
Authors
1 Department of Computer Science, Periyar Arts College, IN
2 Department of Computer Science, Dharmapuram Gnanambigai Government Arts College for Women, IN
3 PG Department of Computer Application, St. Joseph’s College of Arts and Science, Cuddalore, IN
Source
ICTACT Journal on Communication Technology, Vol 14, No 4 (2023), Pagination: 3063-3070Abstract
The major Objective of this research paper is to design the Mobile Smart Device Digi Cash Intrusion Detection Framework (MSDDID) for assessing Intrusion Detection (ID) techniques and evaluating ID parameters that has to be rectified for enhancing the security of Digital Cash Transactions in Mobile Smart devices. The Research examined the Intrusion Detection dataset with 41 predictive features and 1 class feature for evaluating prediction in its novel form. The Framework was examined in WEKA with RapidMiner for analysis. The Results of classifiers Decision Table (98.7%), Random Forest Tree (99.79%), AdaBoost (94.37%), CART Model (99.61%), LazyIBK (99.44%), Naïve Bayesian (89.66%) signified that Smart devices security in Digi cash transactions could be predicted with refinement of data during transaction as deployed in this research work. The cluster analysis again conformed that num_root, su_attempted and num_compromised were the three parameters predominantly used for intrusions in the network and has to be addressed in the model.Keywords
Intrusion Detection System, Network Security, Intrusion Detection Parameters, Digital Cash Transactions, Mobile Smart Systems.References
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