ENGT 5214 Study Skills and Research Methods Assignment Sample
Module code and Title: ENGT 5214 Study Skills and Research Methods Assignment Sample
Introduction
This report also involves sentiment analysis on the social media platform. In social media use for many people. All people do not belong to the same culture. In social media many people use various types of language. This analysis is also referred to as opinion mining. The sentiment analysis is defined in a body of the texting part using emotional tone. Sentiment analysis is an approach to natural language processing as well as it also refers to the NLP.
To determine the great technique for determining as well as specified options for a product, service as well as idea. For the data mining technique, it uses machine learning as well as ML as well as Artificial Intelligence as well as AI for the information of a subjective type as well as those two processes used that is machine learning as well as artificial intelligence.
The sentiment analysis is helpful to the company for jotting the positive sights as well as random text that comes from many online resources that involve blog posts as well as emails as well as many social media chatting groups as well as comments as well as social media blogging channels. By implementing the various types of rule involve many social types of activities.
Aim and Objectives
For the sentiment analysis of a text research for the data mining applied on the machine learning as well as artificial intelligence applies the mix to identify the information to extract to the subject information for the text files as well as review (Madhi et,al,2021). For the opinion mining as well as focusing on the analysis of the special use of the teams (Bonta, et,al,2019).
For the sentiment of the emotional behavior special uses of some terms. The goal of sentiment analysis is the same for actually knowing the visitor’s term that is based on object analysis. The analysis of sentiment on the documentation as well as it is dependent on the sentence levels (Han,et,al,2020). For the sentiment analysis the classified to the actual subject for the emotional attachment (Alsaeedi,et,al,2019). For importance to be determined for the subject. Choosing the sentence of the suggestive name is very identical as well as it is an appointment to express somebody’s characteristics. The actual aim of sentiment analysis on the social media platform is a process to identify the system (Saltman et,al,2021).
For the sentiment analysis defining the sentence quality as well as it is not defined the sentiment has to be determined. The structure of sentence as well as the characteristics of the sentence it does the positive as well as negative as well as the character of the subject is neutral. For the actual object of the expression that is the entry part depends on the subject quality (Hassan et,al,2020).
For engaging the facial expression depends on the particular objective. In the expression it also depends on the people’s mind condition. The facial expression describes the user’s mental condition. Social media is a platform where people can express their personal insights (Verma et,al,2022). For the many events as well as characteristics which also depend on the various kinds of person. In the social media platform various types of people use for various purposes.
Literature Review
According to Ahuja,et,al,2019, the viability of discourse while countering radicalism on the web. Most evaluations of counter-discourse are restricted in scope. This white paper, a commitment metric, inspects two models to all the more likely measures conduct changes and feeling investigation. The first is through an association among Facebook and an enemy of revolutionary NGOs.
Openness to low predominance, high gamble target bunches in which they are involved Islamic fanatic psychological militant substance. The subsequent model depends on this web-based security mediation approach and divert technique by means of a pursuit based “Find support” module that sidetracks search terms connected with Whitesupremacy and NeoNazi to unengaged NGOs.
According to de et,al, 2020, lately, assessments put together presents with respect via web-based entertainment have rebuilt business and general assessment, and feelings have been displayed to influence our social and political frameworks. Assessment is integral to practically all human action, as it is the main component impacting our way of behaving. At the point when we need to pursue a choice, we for the most part need to know the assessments of others. Each association or organization generally needs to track down clients and popular assessment on their items and administrations.
Thus, it is important to gather and research conclusions on the web. In any case, finding and checking locales on the Internet and removing surveys stays an overwhelming undertaking. This is on the grounds that each site ordinarily contains an enormous number of remarks, and it is challenging for the typical human peruser to recognize the extremity of each audit and sum up the sentiments contained in. Consequently, mechanized opinion examination is expected to observe extremity esteems and arrange surveys as certain or negative.
According to Wahid,et,al,2019, the traditional bibliometric methodologies use quantitative indexes based on citation data to assess the effect of research. However, because of the lag time associated with citation-based indices, it may take years to fully appreciate an article’s significance. The goal of this study is to determine the early effect of research publications by analyzing the attitudes expressed in tweets about them.
We contend that papers referenced in positive or neutral tweets have a greater impact than those not cited at all or in negative tweets. Researchers upgraded the SentiStrength programme by adding additional opinion-bearing terms to its sentiment lexicon relevant to scientific disciplines.
According to Han,et,al,2020, the sentiment analysis on the Twitter platform introduces the direct as well as indirect analysis influenced by the value of the market price that actually depends on Bitcoin. The all experienced is involved with predicting the volatile rate for Bitcoin on the Twitter platform. In this report for civilized the to the find of Bitcoin value for analysis the various types of sources for introducing the actual method for the twitter platform.
The collecting of the Bitcoin value in the various types of social media platforms are obtained. The collecting of the Bitcoin value is dependent on classification for the negative tweeter image. Analysis of Bitcoin is divided into the two types of tweets. For the positive tweets for the RNN value is obtained for the value is 81.39% as well as the full predicted value is predicted. The full assumed accuracy value using RNN is given the value 77.62%. The actual value for the tweets actually depends on the time frame. Cryptocurrency for the topic is based on the currency for the Government for the cryptography for the blockchain.
According to Alsaeedi, et,al,2019, the full world is actually being converted quickly under the actual development for the form with the present world. The use of the Internet has to be developed for an actual need for an actual field of study. In the Internet, using the platform is for the everyday issues of the platform. For admissions of the social field for the actual analysis is to prepare the sentiment analysis for the task.
For the consideration of the analysis of opinions for social issues. The social platform is texted behind the topics. The voice of the social media platform is actually established for selling the product as well as it also depends on the Twitter platform. For analyzing the report tweets is also the actual analysis for the opinions. For the sentiment analysis of Twitter to export the optimizing solutions for the risk.
According to Madhi et,al,2021, the sentiment analysis of twitter is all about the Bitcoin that is influenced as well as depends on the market value for the Bitcoin value. For analyzing the full market price that is under the specialized process.
According to Erin et al. 2020, the community of CVE and counterterrorism has long questioned the Counter speech effectiveness in countering online extremism. While most of the county speech evaluation depends on engagement metrics and limited reach, this paper helps in exploring both the models for better change in behavioral measure as well as analysis which is sentimental.
Conducted through partnerships between counter-extremism and Facebook NGOs, the initial model uses testing of A/B for analyzing the Counter speech effects of exposure on audiences who have high-risk-low-prevalence and constantly engaging with content of Islamist extremist terrorist.
Methodology
The methodology that will be used here is a secondary method. In this method, websites and articles will be used to gather data for this research (Ahuja,et,al,2019). Social media is the most used communication method in which everyone conveys their feelings. For this reason, scraping social media data can be beneficial for different organizations. The goal of this phase will be to determine the methodology used to conduct research, if the approach was appropriate, and whether the accuracy of the results was maintained (de iet,al,2020).
A strategy for projecting the future value of a company’s stock is stock market forecasting. Nowadays, numerous media such as websites, Twitter, Facebook, blogs, and others provide a lot of vital financial market information. In general, two factors influence the price of a stock. The first is a necessary component, whereas the second is a technical consideration.
The most important factor is statistical data from a corporation. It includes reports, a corporation’s economic status, financial statements, payments, and policies of firms whose stock is traded. The system of any kind of investigation as well as procedures chosen by the individual analysts are referred to as the plan of any kind of investigation(Wahid,et,al,2019).
The research plans are beneficial and intriguing since they were chosen by scientists, allowing them to apply the types of approaches that are practical and suited for the investigation in order to build up the focus as a fruitful one in the future as well. For the most part, there are four types or types of examination plans that would be beneficial and convincing for scientists to sort out or figure out various types of results.
Research methods are also items that are related to or specifically related to the investigation. Research strategies are the kinds of things that refer to systems, cycles, methods, or whatever else that is related to or associated with the research issue and is effective, successful for determining or sorting out the legitimate end. Scientists should be able to collect knowledge using effective exploratory approaches. There are several types of examination techniques that are often used by professionals all around the world.
Ethical consideration
Ethics in research is important and should be followed by researchers in every study. Some of the exploration ethics are sincerity, which means that every piece of information or data obtained by the scientists should be accurately accounted for. The data or information, as well as the results, tactics, systems, and current state of distributions, must all be carefully and honestly addressed.
Risk for sentiment analysis
The sentiment analysis for the number to review the online platform for the feelings of the express on the directed way. The actual aim for an effective process to differentiate the target for the sentiment. For the worldwide organizations for the successful for the manage for need that visualize the media as well as it is also streamed for learning process. For the social media posts as well as the costly the similar projects of the social media users.
Work Plan
The future work plan of sentiment analysis of social media platforms is going for the continuation of analysis for the human perspective as well as it also depends on the human mind control. For the future plan in a way of deeper as well as broader highlights from the sentiment analysis.
The sentiment analysis is better because social media has developed the excess of the emotional as well as expressive manner. It is enjoyable for the content of showing the actual facial expression. For sentiment analysis the average social media user that is fun as well as it is available to the media. For sentiment analysis is a silly feature for the social media user to give their responses.
However, if a person is in favor of data in a social media platform. For the sentiment analysis they give the media data for the data behind the scenario. The sentiment analysis is organized and has to be a large contributing factor that achieves the actual focusing.
For the advertisements of the social media partner is always to develop the balance with the work field as well as social media users. The exact process to fulfill the most exciting target. For developing the sentiment analysis process for future purposes it can visualize the actual emotions of people. The audience on the surface analysis it is great to help the main wondering. For the searching of this process it is helpful to introduce the media data.
Conclusion
This report concluded that sentiment analysis on social media platforms also depends on the people’s mental condition as well as it also depends on the culture of personal behavior. The sentiment analysis is a field of actual study to analyze the behavior of personal emotions. It is a fundamental problem for the analysis behavior for sentiment. This report is also involving the actual problem of sentiment analysis as well as behavior analysis. This report also categorized emotional behavior.
Many online platforms are also discussed in the detailing format as well as it is the actual description for the analyzed persons. For the level of review categorized for the high-level analysis as well as it is compared to high level analysis.The process of sentiment polarity level is proposed for each level of categorization. For the categorized for the review level for the performed in the certain level.
For each and every step the experiments level is also suggested for the categorized for the sentence level as well as experiments of the sentiment analysis is also performed the review level of organization. For the sentiment analysis is actually held for the business part which is continued with the help of sentiment analysis. The sentiment of analysis is actual a most important as well as positive object for the online business as well as it is also looking for measurement the attitudes as well as it is also involve the people’s feelings as well as this analysis is also depends on people’s mind condition.
Reference list
Journal
Verma, S. and Singh, V., 2022. ORGANIZATIONS AND EMPLOYEES SAY “I DO” TO WORK FROM HOME DURING THE PANDEMIC: A SENTIMENT ANALYSIS OF TWITTER. JISTEM-Journal of Information Systems and Technology Management, 19.
Hassan, S.U., Aljohani, N.R., Idrees, N., Sarwar, R., Nawaz, R., Martínez-Cámara, E., Ventura, S. and Herrera, F., 2020. Predicting literature’s early impact with sentiment analysis in Twitter. Knowledge-Based Systems, 192, p.105383.
Saltman, E., Kooti, F. and Vockery, K., 2021. New models for deploying counterspeech: Measuring behavioral change and sentiment analysis. Studies in Conflict & Terrorism, pp.1-24.
Bonta, V. and Janardhan, N.K.N., 2019. A comprehensive study on lexicon based approaches for sentiment analysis. Asian Journal of Computer Science and Technology, 8(S2), pp.1-6.
Wahid, M.F., Hasan, M.J. and Alom, M.S., 2019, September. Cricket sentiment analysis from Bangla text using recurrent neural network with long short term memory model. In 2019 International Conference on Bangla Speech and Language Processing (ICBSLP) (pp. 1-4). IEEE.
Sharma, C., Whittle, S., Haghighi, P.D., Burstein, F. and Keen, H., 2020. Sentiment analysis of social media posts on pharmacotherapy: A scoping review. Pharmacology research & perspectives, 8(5), p.e00640.
Madhi, H.A.B. and Alhammad, M.M., 2021. What Drives Airbnb Customers’ Satisfaction in Amsterdam? A Sentiment Analysis. International Journal of Advanced Computer Science and Applications, 12(6).
Alsaeedi, A. and Khan, M.Z., 2019. A study on sentiment analysis techniques of Twitter data. International Journal of Advanced Computer Science and Applications, 10(2), pp.361-374.
Pant, D.R., Neupane, P., Poudel, A., Pokhrel, A.K. and Lama, B.K., 2018, October. Recurrent neural network based bitcoin price prediction by twitter sentiment analysis. In 2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS) (pp. 128-132). IEEE.
Han, Y., Liu, M. and Jing, W., 2020. Aspect-level drug reviews sentiment analysis based on double BiGRU and knowledge transfer. IEEE Access, 8, pp.21314-21325.
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