The hyperparameters for the SGD were tuned using GridSearchCV. https://doi.org/10.1016/J.ELECTSTUD.2015.11.017, Cambria E, Speer R, Havasi C, Hussain A (2010) SenticNet: a publicly available semantic resource for opinion mining. Lect Notes Eng Comput Sci 1:472–476, Kumar A, Sebastian TM (2012) Sentiment analysis: a perspective on its past, present and future. The attention was largely shifted to non-probability procedure. Artif Intell Rev. IEEE, pp 1–8. The analysis usually uses the classification of tweets containing public sentiment about the issue. https://doi.org/10.18653/v1/P17-1068, Priyavrat, Sharma N (2018) Sentiment analysis using tidytext package in R. In: 2018 first international conference on secure cyber computing and communication (ICSCCC). https://doi.org/10.1109/HICSS.2012.607, Song M, Kim MC, Jeong YK (2014) Analyzing the political landscape of 2012 Korean presidential election in Twitter. The emergent theory of marketplace sentiments (1) advances a sociocultural perspective on consumer emotion, (2) elevates the theoretical significance of emotional observations in cultural studies, (3) offers a sentiment-based understanding of the power of ideology, (4) indicates how activist sentiments can paradoxically benefit from brand cooptation, and (5) calls for human input in big data sentiment analysis. Social media has brought about rapid change in society, from our social interactions and complaint systems to our elections and media outlets. The paper also highlighted some state-of-the-art studies related to sentiment analysis using deep learning and word embedding methods. J Ambient Intell Humaniz Comput 11:97–117. Multimed Tools Appl. - 91.184.52.33. During the COVID-19 global pandemic lockdown period, users expressed their concerns about the crises via social networks. We encourage the submission of long and short papers including novel research contributions, system demonstration papers, negative results, and opinion pieces including, not restricted to the following topics, however, all related to subjectivity, sentiment, emotion, opinion mining and social media analysis: View Social Media Sentiment Analysis Research Papers on Academia.edu for free. It is increasingly used by individuals and organizations in both the public and private sectors. In: Proceedings of the National conference on artificial intelligence. Int J Adv Comput Sci Appl 8:424–433. All implementations are done by using C# programming language in .NET 4.5 framework, and MS-SQL Server 2014 database management system is employed for data storage. https://doi.org/10.1145/1871985.1871993, Rojas-Barahona LM (2016) Deep learning for sentiment analysis. https://doi.org/10.1177/0165551517698298, Esuli A, Sebastiani F, Moruzzi VG (2006) SENTIWORDNET: a publicly available lexical resource for opinion mining. https://doi.org/10.1007/s12559-017-9503-3, Asiaee TA, Tepper M, Banerjee A, Sapiro G (2012) If you are happy and you know it... tweet. Int J Intell Syst Appl 4:1–14. IEEE Trans Multimed 17:2271–2280. Academia.edu no longer supports Internet Explorer. IEEE, pp 1345–1350. OpenAI Blog 1:9, Rani S, Kumar P (2019) Deep learning based sentiment analysis using convolution neural network. It also provide future directives for this field deliberating about the areas which need due attention. https://doi.org/10.1109/ICCC.2015.7432974, Jose R, Chooralil VS (2016) Prediction of election result by enhanced sentiment analysis on Twitter data using classifier ensemble approach. IEEE, pp 1–6. We experimented the proposed predictive framework with stock data obtained from the Ghana Stock Exchange (GSE) between January 2010 and September 2019, and predicted the future stock value for a time window of 1 day, 7 days, 30 days, 60 days, and 90 days. The kinds of data analysis which is attained from the news reports, user reviews, social media updates or microblogging sites is called sentiment analysis which is also known as opinion mining. https://doi.org/10.23919/SEEDA-CECNSM.2018.8544919, Pagolu VS, Reddy KN, Panda G, Majhi B (2016) Sentiment analysis of Twitter data for predicting stock market movements. The field of text sentiment analysis provides a unique indication of the electorate’s response towards political issues. Our system was ranked 4th in Tamil-English with a weighted average F1 score of 0.62 and 9th in Malayalam-English with a score of 0.65. However, overall the use of the Naive Bayes method has a good performance to classify tweets with an accuracy rate of 92.2% Abstrak Pemilihan kepala daerah (Pilkada) serentak 2020 di tengah pandemic COVID-19 mulai ramai di bicarakan mulai dari dunia nyata maupun di dunia maya, khususnya di media sosial Twitter. This survey paper outlines the evaluation of sentiment analysis techniques and tries to edify the contribution of the researchers to predict election results through social media content. Introduction Attention towards sentiment analysis has been flourishing over the last two decades because of the immense popu-larity of social media. IEEE, pp 638–641. In: Proceedings of the second international workshop on issues of sentiment discovery and opinion mining - WISDOM ’13. Sentiment analysis is a kind of data mining where you measure the inclination of people’s opinions by using NLP (natural language processing), text analysis, and computational linguistics. https://doi.org/10.1109/TMM.2015.2487863, Yue L, Chen W, Li X et al (2018) A survey of sentiment analysis in social media. Product reviews are a User Generated Content (UGC) feature which describes customer satisfaction. IEEE Intell Syst 32:70–75. https://doi.org/10.1145/2938640, Goularas D, Kamis S (2019) Evaluation of deep learning techniques in sentiment analysis from Twitter data. IEEE Intell Syst 30:10–17. https://doi.org/10.1108/IntR-06-2012-0114, Khan FH, Bashir S, Qamar U (2014) TOM: Twitter opinion mining framework using hybrid classification scheme. The review also reveals that majority of the scholars found it difficult to select appropriate samples using probability procedure. ACM Press, New York, USA, pp 430–438. https://doi.org/10.1111/j.1740-9713.2015.00823.x, Medhat W, Hassan A, Korashy H (2014) Sentiment analysis algorithms and applications: a survey. Soc Sci Comput Rev 31:649–679. Agarwal B, Mittal N (2016) Prominent feature extraction for review analysis: an empirical study. This work presents and assesses the power of various volumetric, sentiment, and social network approaches to predict crucial decisions from online social media platforms. Naive Bayes Classifier dikombinasikan dengan fitur yang dapat mendeteksi pembobotan menggunakan probabilitas. In questa sede si cerca di metterne in luce le caratteristiche principali, sulla base di una valutazione del sentiment attenta ad età e gender dei recensori. 1. https://doi.org/10.1109/ICCAR.2017.7942788, Hemmatian F, Sohrabi MK (2017) A survey on classification techniques for opinion mining and sentiment analysis. In: 2019 international conference on deep learning and machine learning in emerging applications (Deep-ML). In this context, we proposed the Probabilistic Latent Semantic Analysis (PLSA) method to produce a hidden topic. Chauhan, P., Sharma, N. & Sikka, G. The emergence of social media data and sentiment analysis in election prediction. https://doi.org/10.3745/JIPS.04.0120, Tripathy A, Agrawal A, Rath SK (2016) Classification of sentiment reviews using n-gram machine learning approach. Inf Process Manag 57:102034. https://doi.org/10.1016/j.ipm.2019.04.002, D’Andrea A, Ferri F, Grifoni P, Guzzo T (2015) Approaches, tools and applications for sentiment analysis implementation. Internet Res 23:544–559. The main objective of this book is to encourage researchers to explore the key concepts of data mining and utilizing them on online social media platform. IEEE, pp 577–580. https://doi.org/10.1080/00437956.1954.11659520, Hassan A, Mahmood A (2017) Deep learning approach for sentiment analysis of short texts. https://doi.org/10.1109/HICSS.2015.202, Kim J, Cha M, Lee JG (2017) Nowcasting commodity prices using social media. Soft Comput. In: 2016 IEEE international conference on Big Data (Big Data). 2007) Investor Sentiment is di cult to directly measure. https://doi.org/10.1145/3325112.3325252, Budiharto W, Meiliana M (2018) Prediction and analysis of Indonesia Presidential election from Twitter using sentiment analysis. https://doi.org/10.1109/MIS.2015.17, Tsakalidis A, Aletras N, Cristea AI, Liakata M (2018) Nowcasting the stance of social media users in a sudden vote: the case of the Greek referendum. In this study, a novel product search engine system which supports “find the best products for a given category” type queries is proposed. Consumers learn, experience, and communicate sentiments to commune and individuate in society. Data-centric systems and applications. Soc Sci Comput Rev 33:3–20. https://doi.org/10.1080/02688697.2017.1354122, Perez Rosas V, Mihalcea R, Morency LP (2013) Multimodal sentiment analysis of spanish online videos.

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