Enter the world of sentiment analysis. https://doi.org/10.1145/2502069.2502072, Mudinas A, Zhang D, Levene M (2012) Combining lexicon and learning based approaches for concept-level sentiment analysis. This fact makes the event interesting as a multi-hazard phenomenon. The analysis usually uses the classification of tweets containing public sentiment about the issue. In: AAAI fall symposium series, pp 14–18, Cambria E, Ebrahimi M, Hossein Yazdavar A et al (2017) Challenges of sentiment analysis for dynamic events. Rather than let your customers’ emotions fall by the wayside, brands today can translate those feelings into actionable business data. In: Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics). This paper is written for (social science) researchers seeking to analyze the wealth of social media now available. Soft Comput. In: Proceedings of the 2017 IEEE/ACM international conference on advances in social networks analysis and mining 2017. Correspondence to Our use of language-specific Soundex to harmonise the spelling variants in code-mixed data appears to be a novel application of Soundex. Sentiment Analysis for Arabic in Social Media Network: A Systematic Mapping Study. Social media monitoring has been growing day by day so analyzing of social data plays an important role in knowing customer behavior. https://www.pewresearch.org/about/ (Last accessed on 17 Feb. 2020). With the expansion in tenders on the Internet and social media, Arabic Sentiment Analysis (ASA) has assumed a significant position in the field of text mining study and has since remained used to explore the sentiments of users about services, various products or topics conversed over the Internet. IEEE, pp 1345–1350. Artif Intell Rev. Presenting Tambr, a new software automatically generates musical pieces from text and for translating literature into sound using multiple synthesized voices selected for the way in which their timbre relates to the meaning and sentiment... Presenting Tambr, a new software automatically generates musical pieces from text and for translating literature into sound using multiple synthesized voices selected for the way in which their timbre relates to the meaning and sentiment of the topics conveyed in the story. Sentiment analysis critically encourages organizations to determine customers’ likes and … http://snap.stanford.edu/social2012/papers/shi.pdf. In: ICWSM 2010 - Proceedings of the 4th international AAAI conference on weblogs and social media, pp 122–129, Oikonomou L, Tjortjis C (2018) A method for predicting the winner of the USA presidential elections using data extracted from Twitter. The review of 32 journal articles shows that most of the scholars developed own and used Internet-enabled software for exploration of big data in the new media. https://doi.org/10.1007/s10115-018-1236-4, Yusof NN, Mohamed A, Abdul-Rahman S (2015) Reviewing classification approaches in sentiment analysis. In: 20th Annual international conference on digital government research. IEEE, pp 64–67. Immediate online access to all issues from 2019. Facebook non è solo un social network in cui postare i propri pensieri, commentare post o intrattenersi con i propri amici: nelle pagine di hotel e ristoranti, gli utenti sono anche in grado di scrivere recensioni. IEEE, pp 4950–4957. https://doi.org/10.1109/ISPCC.2017.8269729, Ain QT, Ali M, Riaz A et al (2017) Sentiment analysis using deep learning techniques: a review. pp 201–208, Makazhanov A, Rafiei D, Waqar M (2014) Predicting political preference of Twitter users. However, they were still useful as a proxy estimation of damages in some areas of Zagreb and surroundings. In this respect, the automatic classification and information extraction from users’ comments, also known as sentiment analysis (SA) becomes vital to offer users the best responses to users’ queries, based on their preferences. Acta Polytech Hung 12:87–108, Appel O, Chiclana F, Carter J, Fujita H (2016a) A hybrid approach to sentiment analysis. In: Web data mining. https://sentic.net/ (Last accessed on: 13 March 2020). https://doi.org/10.1145/2346676.2346681, Mumtaz D, Ahuja B (2018) A lexical and machine learning-based hybrid system for sentiment analysis. Expert Syst Appl 57:117–126. Sentiment analysis has been increasingly popular in the present digital era which attempts to analyse the consumer reviews acquired from websites, blogs and social media platforms. Defined as... From outrage at corporations to excitement about innovations, marketplace sentiments are powerful forces in consumer culture that transform markets. ... 40,359 Korean posts on childhood vaccination were collected from 27 social media channels between January and December 2015. The focused crawler is used to crawl product information from various e-commerce sites; the record linkage system determines the identical products that are crawled from different e-commerce sites; the sentiment analyzer classifies users’ reviews about the products as positive or negative so that our product search engine can decide which product is the best for a given category; and the query engine takes the user queries and displays the result. This paper presents details and analysis of this monitoring and how it may help understand the impacts of an earthquake. Hutto Eric Gilbert Georgia Institute of Technology, Atlanta, GA 30032 cjhutto@gatech.edu gilbert@cc.gatech.edu Abstract The inherent nature of social media content poses serious challenges to practical applications of sentiment analysis. https://doi.org/10.1007/s13278-014-0181-9, Appel O, Chiclana F, Carter J (2015) Main concepts, state of the art and future research questions in sentiment analysis. 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. Our approach utilises language features like use of... Theedhum Nandrum is a sentiment polarity detection system using two approaches-a Stochastic Gradient Descent (SGD) based classifier and a Long Short-term Memory (LSTM) based Classifier. Marketplace actors such as activists, brands, and consumers have a variety of motives and methods for producing and reproducing sentiments. ACM Press, New York, USA, pp 1–8. In: Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD ’11. They are mainly online product reviews, general tweets in Tweeter and movie reviews. The Term Frequency-Inverse Corpus Frequency (TF-ICF) method was used for weighting each term list, which had been expanded from each cluster in the document. These issues and trends have created gaps for potential scholars in the field to conduct studies that would contribute to the knowledge base in the big data field. 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. This study maps study results with observations made by the Osservatorio di Pavia, which is an Italian institute of research specialised in media analysis at theoretical and empirical level, engaged in the analysis of political communication in the mass media. Wiley Interdiscip Rev Data Min Knowl Discov 5:292–303. The huge volume of online reviews makes it difficult for a human to process and extract all significant information to make decisions. Product reviews are a User Generated Content (UGC) feature which describes customer satisfaction. Our experiments show that, for our dataset of political tweets, the most accurate NER system, Google Cloud NL, performed almost on par with crowdworkers, but the most accurate ELS analysis system, TensiStrength, did not match the accuracy of crowdworkers by a large margin of more than 30 percent points. Institute of Electrical and Electronics Engineers Inc. pp 494–498. https://doi.org/10.1145/3341161.3343676, Jaidka K, Ahmed S, Skoric M, Hilbert M (2018) Predicting elections from social media: a three- country, three-method comparative study. OpenAI Blog 1:9, Rani S, Kumar P (2019) Deep learning based sentiment analysis using convolution neural network. ACM, New York, USA, pp 763–770. for social networking and share their opinions, feelings or beliefs with others. Social media analytics have proven valuable in numerous research areas as a pragmatic tool for public opinion mining and analysis. ACM Press, New York, USA, pp 1–9. The classification method used in this research is Naive Bayes Classifier (NBC) And Support Vector Machine (SVM). Int J Adv Comput Sci Appl 8:424–433. arXiv:1308.6242, Monti C, Zignani M, Rozza A et al (2013) Modelling political disaffection from Twitter data. Int J Adv Res Comput Sci Softw Eng 2:282–292, Volkova S, Coppersmith G, Van Durme B (2014) Inferring user political preferences from streaming communications. ACM, New York, USA, pp 816–824. https://doi.org/10.1177/0894439311404119, Kalampokis E, Tambouris E, Tarabanis K (2013) Understanding the predictive power of social media. Class concepts were extracted from these terms. https://nodexl.com/ (Last accessed on: 13 March 2020). From there, we can use the public’s general feelings to initiate campaigns based off of their feedback. Semantic Similarity was used to classify topics into five hotel aspects. In: ICWSM 2012 - Proceedings of the 6th International AAAI conference on weblogs and social media, pp 387–390, Anjaria M, Guddeti RMR (2014) A novel sentiment analysis of social networks using supervised learning. Agarwal B, Mittal N (2016) Prominent feature extraction for review analysis: an empirical study. Knowl Inf Syst. The most interesting result of the research is the construction of the sentiment risk factor based on the direct search-based sentiment indicators. In: 2017 9th computer science and electronic engineering (CEEC). IEEE Internet Comput 16:91–94. Significance 12:10–15. Product reviews are a User Generated Content (UGC) feature which describes customer satisfaction. http://sentistrength.wlv.ac.uk/#About (Last accessed on: 13 March 2020). https://doi.org/10.1007/s00500-019-04402-8, Choy M, Cheong MLF, Laik MN, Shung KP (2011) A sentiment analysis of Singapore presidential election 2011 using Twitter data with census correction. IEEE, pp 109–112. https://doi.org/10.1109/MIS.2013.9, Peters M, Neumann M, Iyyer M et al (2018) Deep contextualized word representations. Sentiment Analysis of Social Media Text C.J. ACM Press, New York, USA, pp 791–794. This guidance document predominantly focuses on the use of social media for analysis and research, rather than for communication and engagement. Further, this paper also suggests some future directions in respective election prediction using social media content. 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. This study fills this gap through the analysis of a random sample of 26,905 tweets dealing with the Arab image in Spanish tweets. Sentiment analysis is related to attitude, feelings & emotions for specific purpose (e.g. https://doi.org/10.1007/s12652-020-02423-y, DOI: https://doi.org/10.1007/s12652-020-02423-y, Over 10 million scientific documents at your fingertips, Not logged in https://doi.org/10.1109/MACS.2018.8628445, Bojanowski P, Grave E, Joulin A, Mikolov T (2017) Enriching word vectors with subword information. ACM Press, New York, USA, pp 1602–1606. https://doi.org/10.1145/505282.505283, Sharma A, Dey S (2012) A comparative study of feature selection and machine learning techniques for sentiment analysis. Klasifikasi tweet dalam penelitian ini diperoleh berdasarkan kombinasi antara dua kelas yaitu kelas sentimen dan kelas kategori. The analysis of large amount of data is an exciting challenge for researchers, but it is also crucial for all those who work at different levels in the current information society: https://doi.org/10.1109/BigData.2016.7840818, Shi L, Agarwal N, Agrawal A, et al (2012) Predicting US primary elections with Twitter. The study analyzes the general public's response towards the COVID-19 preventive 21-day lockdown in Indiafrom25 th March2020 to 14 th April 2020.The Indian general public actively responded to lockdown related Twitter hashtags both positively and negatively.The dataset of the lockdown period tweets was analyzed daily to gauge the overall response of the public.The research identified the most frequently used words and word pairs as the highlights of conversations. 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During the COVID-19 global pandemic lockdown period, users expressed their concerns about the crises via social networks. DITENGAH PANDEMIC COVID-19 DENGAN METODE NAÏVE BAYES CLASSIFIER, Assessing Emergency Response and Early Recovery using SA. https://doi.org/10.1109/JCSSE.2016.7748849, Vinodhini G (2012) Sentiment analysis and opinion mining: a survey. arXiv:1108.5520, Chung J, Mustafaraj E (2011) Can collective sentiment expressed on twitter predict political elections? In this respect, the forecasting of election results is an application of sentiment analysis aimed at predicting the outcomes of an ongoing election by gauging the mood of the public through social media. Springer Verlag, pp 469–477. J Big Data 5:1–10. Through the LastQuake app, we obtained the intensity reports from affected people and comments and pictures useful for damage assessment. This paper is focused at sentiment analysis, analyzing work done in various languages, common techniques utilized and the type of data set being employed. Internet Res 23:544–559. https://datasift.com/ (Last accessed on: 13 March 2020). https://doi.org/10.1145/2020408.2020477, Pennebaker JW, Booth RJ, Francis ME (2012) Linguistic inquiry and word count: LIWC2007. Sentiment analysis can be used to quickly analyze the text of research papers, news articles, social media posts like tweets and more. “Pew Research Centre is a nonpartisan fact tank that informs the public about the issues, attitudes, and trends shaping the world. In: Proceedings of the III international workshop on web and text intelligence (WTI), pp 404–413, Skoric M, Poor N, Achananuparp P et al (2012) Tweets and votes: a study of the 2011 Singapore general election. Association for Computational Linguistics (ACL), pp 4171–4186. Association for Computational Linguistics (ACL), pp 455–459, Harris ZS (1954) Distributional structure. It also provide future directives for this field deliberating about the areas which need due attention. Each product review was preprocessed into a term list document. https://doi.org/10.1007/978-981-10-4555-4_11, Ni M, He Q, Gao J (2017) Forecasting the subway passenger flow under event occurrences with social media. Semantic network analysis of vaccine sentiment in online social media can enhance understanding of the scope and variability of current attitudes and beliefs toward vaccines. In: Proceedings of the 13th conference of the European chapter of the association for computational linguistics, pp 53–60, Schoen H, Gayo-Avello D, Takis Metaxas P et al (2013) The power of prediction with social media. Analisis yang dilakukan biasanya menggunakan klasifikasi tweet yang berisi sentimen masyarakat tentang issu tersebut. The huge volume of online reviews makes it difficult for a human to process and extract all significant information to make decisions. https://doi.org/10.1080/01292986.2018.1453849, Jose R, Chooralil VS (2015) Prediction of election result by enhanced sentiment analysis on Twitter data using word sense disambiguation. https://doi.org/10.1145/3269206.3271783, Tumasjan A, Sprenger TO, Sandner PG, Welpe IM (2010) Predicting elections with Twitter: What 140 characters reveal about political sentiment. The case of Zagreb, Croatia, Theedhum Nandrum@Dravidian-CodeMix-FIRE2020: A Sentiment Polarity Classifier for YouTube Comments with Code-switching between Tamil, Malayalam and English, https://github.com/oligoglot/theedhum-nandrum, Il sentiment nelle recensioni di Facebook: età e gender, Sentiment Analysis of 21 daysCOVID-19 Indian lockdown tweets, Machine Learning Based Sentiment Analysis for Text Messages, Performance Comparison of Crowdworkers and NLP Tools on Named-Entity Recognition and Sentiment Analysis of Political Tweets, Predicting Stock Market Price Movement Using Sentiment Analysis: Evidence From Ghana, A Novel Machine Learning System for Sentiment Analysis and Extraction, Computer Science & Information Technology (CS & IT) Computer Science Conference Proceedings (CSCP), Investigating the Image of Entities in Social Media: Dataset Design and First Results, Social media monitoring methods around vaccination: a systematic scoping review, A Product Search Engine Supporting “Best Product” Queries, Sentiment Analysis of Customer Satisfaction using Deep Learning, IRJCS: : International Research Journal of Computer Science. Sentiment analysis or opinion mining of these posts... People use online platforms such as Facebook, Twitter, etc. Sci China Inf Sci 63:1–36. Thematic Analysis (Research Methodology), GENERATING MUSIC FROM LITERATURE USING SENTIMENT ANALYSIS AND TOPIC EXTRACTION, IJIRAE - International Journal of Innovative Research in Advanced Engineering, Sentiment Analysis for on-line Product Reviews. Learn more about Institutional subscriptions. Brands carefully select, calibrate, and broadcast sentiments to entertain consumers and promote products. IEEE, pp 638–641. Chauhan, P., Sharma, N. & Sikka, G. The emergence of social media data and sentiment analysis in election prediction. 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. Knowl Based Syst 108:110–124. Theedhum Nandrum is a sentiment polarity detection system using two approaches-a Stochastic Gradient Descent (SGD) based classifier and a Long Short-term Memory (LSTM) based Classifier. 2007) Investor Sentiment is di cult to directly measure. In: Proceedings of the 27th ACM international conference on information and knowledge management. https://doi.org/10.1080/00437956.1954.11659520, Hassan A, Mahmood A (2017) Deep learning approach for sentiment analysis of short texts. ACM Comput Surv 49:1–41. Building on previous editions, the aim of WASSA 2021 is to bring together researchers working on Subjectivity, Sentiment Analysis, Emotion Detection and Classification and their applications to other NLP or real world tasks (e.g. company, politician) as it is disseminated and viewed on the Internet. The data are sourced by the MarketPsych that analyze information flowing on social media. Soc Sci Comput Rev 30:229–234. This is a preview of subscription content, access via your institution. 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. https://doi.org/10.1109/CEEC.2017.8101605, Wang H, Can D, Kazemzadeh A et al (2012) A system for real-time Twitter sentiment analysis of 2012 US Presidential election cycle. The rapid advancement of web technology has led to an exponential increase in the volume of data present online for internet users. This performance betters the top ranked classifier on this dataset by a wide margin. https://doi.org/10.1145/2896387.2896396, Elshendy M, Fronzetti Colladon A, Battistoni E, Gloor PA (2018) Using four different online media sources to forecast the crude oil price. In: Proceedings of the fifth international AAAI conference on weblogs and social media. to the community through LRE map for further research. product prediction). We tested several commercial and open source tools. Applying SA we identified the most affected areas, the damages in the non-structural elements in hospitals, the support of collaborative networks for the evacuation of patients and the role of Ministers in the early recovery. https://doi.org/10.18653/v1/n18-1202, Preoţiuc-Pietro D, Liu Y, Hopkins D, Ungar L (2017) Beyond binary labels: political ideology prediction of Twitter users. ... Upload an image to customize your repository’s social media preview. Thus, we recorded an increase in prediction accuracy as several stock-related data sources were combined as input to our prediction model. Tax calculation will be finalised during checkout. In: Proceedings of the 2012 ACM research in applied computation symposium on—RACS’12. The classification of tweets in this study was obtained based on a combination of two classes namely sentiment class and category class. IEEE, pp 1966–1971. https://doi.org/10.1109/MIS.2017.3711649, Çano E, Morisio M (2018) A deep learning architecture for sentiment analysis. arXiv:1810.04805, Elghazaly T, Mahmoud A, Hefny HA (2016) Political sentiment analysis using Twitter data. 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: https://doi.org/10.1162/tacl_a_00051, Bose R, Dey RK, Roy S, Sarddar D (2019) Analyzing political sentiment using Twitter data. This paper also discusses the platform and tools for social media analysis such as business toolkit, scientific programming tools, monitoring tools and feature analysis tools. https://doi.org/10.1109/SCOPES.2016.7955659, Pang B, Lee L (2008) Opinion mining and sentiment analysis. In: Proceedings of the 2018 conference of the North American chapter of the association for computational linguistics: human language technologies, volume 1 (Long papers). https://doi.org/10.1109/HICSS.2014.282, Ahuja R, Gupta R, Sharma S et al (2017) Twitter based model for emotional state classification. The growing importance of sentiment analysis coincides with the popularity of social network platforms, such as Facebook, Twitter, and Flickr. https://doi.org/10.1145/2766462.2767833, Gayo-Avello D (2011) Don’t turn social media into another “Literary Digest” poll. https://twiplomacy.com/blog/twiplomacy-study-2018/ (Last accessed on: 17 Feb. 2020).
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