Dissertations / Theses on the topic 'Sentiment analytics'
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Doherty, Amy Josephine. "Understanding Web Sentiment Analytics and Visualization, A Social Media Analysis." Thesis, The University of Arizona, 2014. http://hdl.handle.net/10150/320061.
Full textShen, Chao. "Text Analytics of Social Media: Sentiment Analysis, Event Detection and Summarization." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1739.
Full textYu, Xiang. "Analysis of new sentiment and its application to finance." Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/9062.
Full textBouayad, Lina. "Analytics and Healthcare Costs (A Three Essay Dissertation)." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5876.
Full textPiksina, Olga, and Patricia Vernholmen. "Coronavirus-Related Sentiment and Stock Prices : Measuring Sentiment Effects on Swedish Stock Indices." Thesis, KTH, Fastigheter och byggande, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-276759.
Full textDenna studie undersöker den effekt coronavirus-relaterat sentiment haft på avkastningen på svenska aktieindex under coronaviruspandemin. Vi studerar avkastningen på large cap- och small cap-prisindexen OMXSLCPI och OMXSSCPI under perioden 2 januari 2020 – 30 april 2020. Proxier för coronavirus-sentiment konstrueras från nyhetsartiklar som klustrats i ämnen genom latent Dirichlet-allokering och poängsatts genom sentimentanalys. Sentimentproxiernas påverkan på aktieindexen mäts sedan med en dynamisk multipel regressionsmodell. Resultaten visar att proxierna som representerar fundamentala förändringar i vår modell — svensk politik och ekonomisk policy — har en starkt signifikant inverkan på avkastningen på båda indexen, vilket är konsekvent med finansiell teori. Vi finner även att sentimentproxierna sport och spridning av coronaviruset är statistiskt signifikanta i sin påverkan på svenska aktiepriser. Detta innebär att coronavirus-relaterade nyheter påverkade marknadssentiment i Sverige under undersökningsperioden och skulle kunna användas för att upptäcka arbitrage. Slutligen visas mängden sentimentframkallande nyheter publicerade per dag ha en inverkan på aktieprisvolatilitet.
Aring, Danielle C. "Integrated Real-Time Social Media Sentiment Analysis Service Using a Big Data Analytic Ecosystem." Cleveland State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=csu1494359605127555.
Full textBelau, Francini Scipioni. "Uma proposta de representação linguístico-computacional da negação com vistas à análise de sentimentos em contexto de ensino e aprendizagem on-line." Universidade do Vale do Rio dos Sinos, 2017. http://www.repositorio.jesuita.org.br/handle/UNISINOS/6090.
Full textMade available in DSpace on 2017-03-15T16:53:11Z (GMT). No. of bitstreams: 1 Francini Scipioni Belau_.pdf: 2278562 bytes, checksum: 806e6ee479b7b02ba595eb0759a37f05 (MD5) Previous issue date: 2017-01-11
Gvdasa - Inteligência Educacional
A temática deste trabalho estabelece um diálogo entre as áreas da educação a distância, linguística e processamento automático das línguas naturais (PLN). A proposta é responder às seguintes questões norteadoras: (i) como a negação da emoção se manifesta na superfície da língua? E (ii) que regras computacionais expressam a negação da emoção?. A metodologia do trabalho segue o proposto por Dias-da-Silva (2006), que organiza os trabalhos em PLN em três domínios de investigação complementares: (i) linguístico, (ii) linguístico-computacional e (iii) computacional. No primeiro domínio, o linguístico, descreve-se o fenômeno da negação e o seu uso. No domínio linguístico-computacional, vamos representar os padrões percebidos para orientar os especialistas a codificarem essas regras em uma linguagem computacional. Para propor a descrição linguístico-computacional dos modos de expressão da negação, a partir de um corpus construído em contexto de ensino a distância com base nos relatos diários e fóruns dos alunos, utilizamos como base a teoria abordada por Maria Helena de Moura Neves (2011). A etapa computacional, que prevê a implementação do sistema, é própria do informata e não será contemplada neste trabalho, será realizada por grupo de pesquisa parceiro em colaboração com a empresa GVDasa. Ao todo foram criadas 11 regras linguístico-computacionais que possibilita dar conta das propriedades linguísticas identificadas ao responder a questão (i) de pesquisa. As regras visam a contribuir para que um sistema computacional possa localizar os fenômenos da negação em textos e verificar a existência de inversões de polaridade e emoção.
The thematic of this work establishes a dialogue between the fields of distance learning, linguistics, and natural language processing (NLP). The proposal is to answer the following guiding questions: (i) how does the negation of emotion manifest itself on the surface of the language? and (ii) which computational rules express the negation of emotion? The methodology of this work follows the proposed by Dias-da-Silva (2006), who organizes the works in NLP in three complementary domains of investigation: (i) linguistics, (ii) computational-linguistics, and (iii) computational. In the first domain, the linguistic domain, the phenomenon of denial and its use is described. In the linguistic-computational domain, we will represent the perceived patterns in order to guide the experts to encode these rules in computational language. In order to propose the linguistic-computational description of the forms of expression of negation, through a corpus built in a distance learning context based on daily reports and students’ forums, we take as a base the theory approached by Maria Helena de Moura Neves (2011). The computational phase which forecasts the implementation of the system is pertinent to the computing technician and it will not be contemplated in this work, but it will be performed by a partner research group in collaboration with the GVDasa company. Altogether, 11 linguistic-computational rules were created that make it possible to account for the linguistic properties identified when answering the research question (i). The rules aim to contribute with a computational system to locate the phenomenon of negation in texts and verify the existence of inversions of polarity and emotion.
Bin, Saip Mohamed A. "Big Social Data Analytics: A Model for the Public Sector." Thesis, University of Bradford, 2019. http://hdl.handle.net/10454/18352.
Full textUniversiti Utara Malaysia
Ruan, Yiye. "Joint Dynamic Online Social Network Analytics Using Network, Content and User Characteristics." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1420765022.
Full textRenault, Thomas. "Three essays on the informational efficiency of financial markets through the use of Big Data Analytics." Thesis, Paris 1, 2017. http://www.theses.fr/2017PA01E009/document.
Full textThe massive increase in the availability of data generated everyday by individuals on the Internet has made it possible to address the predictability of financial markets from a different perspective. Without making the claim of offering a definitive answer to a debate that has persisted for forty years between partisans of the efficient market hypothesis and behavioral finance academics, this dissertation aims to improve our understanding of the price formation process in financial markets through the use of Big Data analytics. More precisely, it analyzes: (1) how to measure intraday investor sentiment and determine the relation between investor sentiment and aggregate market returns, (2) how to measure investor attention to news in real time, and identify the relation between investor attention and the price dynamics of large capitalization stocks, and (3) how to detect suspicious behaviors that could undermine the in-formational role of financial markets, and determine the relation between the level of posting activity on social media and small-capitalization stock returns. The first essay proposes a methodology to construct a novel indicator of investor sentiment by analyzing an extensive dataset of user-generated content published on the social media platform Stock-Twits. Examining users’ self-reported trading characteristics, the essay provides empirical evidence of sentiment-driven noise trading at the intraday level, consistent with behavioral finance theories. The second essay proposes a methodology to measure investor attention to news in real-time by combining data from traditional newswires with the content published by experts on the social media platform Twitter. The essay demonstrates that news that garners high attention leads to large and persistent change in trading activity, volatility, and price jumps. It also demonstrates that the pre-announcement effect is reduced when corrected newswire timestamps are considered. The third essay provides new insights into the empirical literature on small capitalization stocks market manipulation by examining a novel dataset of messages published on the social media plat-form Twitter. The essay proposes a novel methodology to identify suspicious behaviors by analyzing interactions between users and provide empirical evidence of suspicious stock recommendations on social media that could be related to market manipulation. The conclusion of the essay should rein-force regulators’ efforts to better control social media and highlights the need for a better education of individual investors
Giorgis, Stavros. "Evaluation of Approaches for Representation and Sentiment of Customer Reviews." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-291214.
Full textKlassificeringen av attityd och känsloläge i kundrecensioner är en tillämpning med praktiskt värde för flera företag i marknadsanalysbranschen. Aktuell forskning i språkteknologi har etablerat vektorrum som standardrepresentation för ord, fraser och yttranden, så kallade embeddings. Denna uppsats utvärderar den senaste tidens mest framgångsrika textrepresentationsmodeller jämfört med mer traditionella vektorrum. Utvärdering görs genom att jämföra automatiska analyser med mänskliga bedömningar för kundrecensioner av varierande längd från olika domäner tillhandahållna av ett textanalysföretag. Inom ramen för studien har olika testmängder jämförts och olika sätt att modifera en språkmodells klassficering utan om träning. Alla modeller har också jämförts med avseende på resurs- och tidsåtgång för träning för att hjälpa uppdragsgivaren fatta beslut om vilken teknik som utgör den mest ändamålsenliga utvecklingsvägen för dess driftsatta system.
Knöös, Johanna, and Siri Amanda Rääf. "Sentiment Analysis of MOOC learner reviews : What motivates learners to complete a course?" Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-105919.
Full textFrancia, Matteo. "Progettazione di un sistema di Social Intelligence e Sentiment Analysis per un'azienda del settore consumer goods." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2012. http://amslaurea.unibo.it/3850/.
Full textUřídil, Martin. "Big data - použití v bankovní sféře." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-149908.
Full textCarlos, Karina Castrezana Pinto. "Percepções, sentimentos e fantasias dos pacientes quanto a seus sintomas de escoriação psicogênica." Pontifícia Universidade Católica de São Paulo, 2014. https://tede2.pucsp.br/handle/handle/15324.
Full textCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
The present study aimed at observing the perceptions, feelings and fantasies of patients in relation to their symptoms of psychogenic excoriation. The population consisted of 48 people, 28 of the control group and 20 of the experimental group, referred by the city clinic of the University of Mogi das Cruzes. Both groups answered a form of characterization and Beck Anxiety Inventory. The second group also answered a semi structured interview, the technical drawing of the human figure, guided imagery and thematic design. The method of analysis of the results was quantitative for anxiety and the form of characterization in both groups, and qualitative analysis was intended only to other techniques applied in the experimental group. The analysis was based on assumptions of Analytical Psychology. It was concluded that stressful situations and conflict contributed to the development and aggravation of symptoms and it was observed that feelings of abandonment, neglect and emptiness arising from childhood surfaced for many participants, in which we found evidence of maternal and paternal complexes. A multidisciplinary approach is necessary and psychological intervention is of paramount importance for the development of traumatic content
pacientes quanto a seus sintomas de escoriação psicogênica. A população foi composta de 48 pessoas, sendo 28 do grupo controle e 20 do experimental, indicadas pela Policlínica da Universidade de Mogi das Cruzes. Ambos os grupos responderam ao formulário de caracterização e ao inventário de Beck de ansiedade, sendo que o segundo também respondeu à entrevista semiestruturada, participou das técnicas do desenho da figura humana, da imaginação dirigida e do desenho temático. O método de análise foi quantitativo para os resultados de ansiedade e caracterização da amostra nos dois grupos, e a análise qualitativa se destinou às demais técnicas aplicadas somente no grupo experimental. A análise dos resultados foi baseada em pressupostos da Psicologia Analítica. Concluiu-se que situações estressantes e de conflito contribuíram para o aparecimento e o agravamento dos sintomas e observou-se que sentimentos de abandono, negligência e vazio advindos da infância vieram à tona por muitos participantes, estando presentes evidências dos complexos materno e paterno. Uma atuação multidisciplinar se faz necessária e a intervenção psicológica é de suma importância para elaboração dos conteúdos traumáticos
Tang, Ming-Hsun, and 湯明勳. "The association between news sentiment analytics and system risk." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/4nxch6.
Full text國立政治大學
會計學系
107
With the rapid development of information technology, the Internet has become the fastest and most convenient channel for investors to obtain information. Different from previous investors who made decisions based on investment reports or financial reports. Nowadays investors also based on the "Financial News" further makes investment decisions. Financial news can provide investors with instant information, therefore, plays an important role in delivering information to investors. The main purpose of this study is to explore whether the "sentiment" impact of "Financial News" on investors is closely related to "System Risk". This study assumes that "News Sentiment Analysis" is related to System Risk. Using the financial news related to 51 listed companies in the "Taiwan 50 Index constituents" in the fourth quarter of 2018, with the "Financial Sentiment Dictionary" to collect "Positive and Negative sentimental words" in financial news, it is used to calculate the variables of "Sentimental Tone" and "Quantity of News" related to each model. Finally, the "Multiple Linear Regression" is performed by SAS statistical software to test the relationship between financial News Sentiment Analysis and System Risk. The empirical results show that there is a correlation between "Sentimental Tone" and " Quantity of News" and System Risk, and there is a "Three-day periods" relation between News Sentiment Analysis and System Risk. This study also found that "Negative Sentimental Tone" and the sentiment analysis of "Negative News" has a significant correlation with System Risk.
Ho, Ching-Yuen, and 何正源. "Investor Sentiment Based on Social Analytics Predicts Stock Price." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/s5amcj.
Full text靜宜大學
會計學系
107
Predicting the stock price has attracted much attention from academia and investor. Can the stock price be predicted? Numerous studies tried to use different ways to answer that. Behavioral economics tell us that sentiment can affect individual behavior and decision-making, so can investor sentiment predict the stock price? For answering this, here this study will use a Neural Network to prove the hypothesis that investor sentiment, as measure from Social Big Data (OpView), have predictive effects on the stock price prediction. The result shows that the investor sentiment measured by OpView have predictive effect of stock price prediction in Taiwan, and this effect will increase as the popularity of individual stocks rises.
Pinto, Herbert Laroca Mendes. "Análise de sentimento e desempenho de participantes em MOOC da Universidade Aberta de Portugal." Master's thesis, 2020. http://hdl.handle.net/10400.2/9922.
Full textWriting is a way of recording human expression. During writing, facts and opinions are expressed and stored in information systems. E-learning platforms are educational environments of distance learning and examples of information systems that store facts and opinions. A specific case of e-learning environment is the MOOC (Massive Open Online Course). The objective of this research is to combine four sentiment analysis API (Application program interface), described by Amazon Natural Language, Google Natural Language, IBM Watson Natural Language Understanding, and Microsoft Text Analytics to create a weighted average of these API scores to analyze the polarity of sentiments in a MOOC environment. Another objective of this research is to study if exists the relationship between the polarity of sentiment expressed in the online interventions and the academic achievement of the participants in the Universidade Aberta de Portugal.. The research cites and discusses the related works, classified by technical approaches. The solution is demonstrated with well-defined steps from both the scientific and methodological point of view. A positivist scientific view is used, with rational and qualitative analysis of experimental data, collected from information systems and applied to an already operational environment. The research is evaluated in terms of recall and precision of the algorithmic sentiment analysis, confronted with sentiment classified qualitatively by humans. The conclusions indicate that the combined polarity of sentiment analysis method is valid for performing accurate polarity of sentiment measurements in the MOOC environment and there is no direct relationship between polarity of sentiment and academic achievement of participants from Universidade Aberta de Portugal MOOC´s.
"Event Analytics on Social Media: Challenges and Solutions." Doctoral diss., 2014. http://hdl.handle.net/2286/R.I.27510.
Full textDissertation/Thesis
Doctoral Dissertation Computer Science 2014
Gouveia, Lia Isabel Morais. "Social media analytics : optimizing Facebook campaign’s performance using text mining." Master's thesis, 2019. http://hdl.handle.net/10362/80210.
Full textNos dias correntes, é visível uma crescente utilização das redes sociais, onde as pessoas podem expressar a sua opinião sobre o que sentem relativamente às empresas, aos seus produtos e/ou serviços. Tal facto apresenta uma oportunidade para as empresas entenderem o que+ se fala sobre elas e se tal é positivo ou negativo (Santos & Ramos, 2009). A crescente utilização das redes sociais levou ao aparecimento do Marketing Digital, onde se tenta captar a atenção das pessoas no meio digital. As redes sociais têm um papel essencial neste mesmo, sendo um dos principais canais utilizados para a marca interagir com o público, onde, por exemplo, em campanhas de maior dimensão podem ser realizadas publicações por forma a captar a atenção das pessoas, havendo a necessidade de haver uma análise da performance destas campanhas no meio digital. Como tal, neste projeto, tendo em conta a importância do digital no Marketing, foram extraídos e analisados os dados da empresa JUMIA (empresa de e-commerce) da Nigéria no Facebook, sendo realizadas uma análise de sentimentos e deteção de tópico às duas campanhas de maior dimensão, tendo como objetivo entender qual o sentimento e temática associados a estes mesmos comentários, por forma a analisar a performance das campanhas e a dar recomendações.
There is a growing use of social media in everyday life, where people can express their opinion about what they feel about companies and their products and/or services. This is an opportunity for companies to understand what is said about them and whether this is positive or negative (Santos & Ramos, 2009). The growing use of social media has led to the emergence of Digital Marketing, where companies try to capture people's attention in the digital environment, with social networks being one of the main channels used for the brand to interact with the public. Posts can be carried out in order to capture people’s attention and because of that there should be an analysis of the performance of these campaigns in the digital environment. As such, this project was carried out taking into account the importance of the digital in Marketing. The data of all the posts and comments in JUMIA (e-commerce company) in Nigeria on Facebook were extracted and analyzed, and a sentiment analysis and topic detection were performed at the two campaigns of larger dimension, aiming to understand the feeling and thematic associated to these comments, in order to analyze the performance of the campaigns and to give recommendations.
Banerjee, S., J. P. Singh, Y. K. Dwivedi, and Nripendra P. Rana. "Social media analytics for end-users’ expectation management in information systems development projects." 2021. http://hdl.handle.net/10454/18498.
Full textThis exploratory research aims to investigate social media users’ expectations of information systems (IS) products that are conceived but not yet launched. It specifically analyses social media data from Twitter about forthcoming smartphones and smartwatches from Apple and Samsung, two firms known for their innovative gadgets. Tweets related to the following four forthcoming IS products were retrieved from 1st January 2020 to 30th September 2020: (1) Apple iPhone 12 (6,125 tweets), (2) Apple Watch 6 (553 tweets), (3) Samsung Galaxy Z Flip 2 (923 tweets), and (4) Samsung Galaxy Watch Active 3 (207 tweets). These 7,808 tweets were analysed using a combination of the Natural Language Processing Toolkit (NLTK) and sentiment analysis (SentiWordNet). The online community was quite vocal about topics such as design, camera and hardware specifications. For all the forthcoming gadgets, the proportion of positive tweets exceeded that of negative tweets. The most prevalent sentiment expressed in Apple-related tweets was neutral but in Samsung-related tweets was positive. Additionally, it was found that the proportion of tweets echoing negative sentiment was lower for Apple compared with Samsung. This paper is the earliest empirical work to examine the degree to which social media chatter can be used by project managers for IS development projects, specifically for the purpose of end-users’ expectation management.
Teixeira, Daniel Rocha. "Text Mining Research Project: Internship at Ageas Portugal." Master's thesis, 2021. http://hdl.handle.net/10362/128809.
Full textAs an insurance company, Ageas Portugal has lots of data related to their customers. Usually, most of data used by companies (disregarding few companies that already use advanced machine learning and artificial intelligence techniques) are structured data, that are known as formatted datasets and tables with customer information. But, with the advance of technology, more companies are starting to use their unstructured data, which could be helpful to find insights and achieve goals. From the different data sources in human language form the company has as emails, customer surveys, medical transcriptions and etc., we have agreed an email database would be the best option for the project development. This type of data requires a very thorough data preparation as there are irrelevant parts within emails as signatures and disclaimers, which should be excluded. Analyzing customer’s interaction with the company we could find insights about how to increase sales and reduce churn rate. We have applied two Text Mining techniques (Sentiment Analysis and Topic Classification) and a proof of concept was conducted. It showed that clients who send or are mentioned in emails tend to cancel their policies at higher rate than those without emails, even if the email’s topic is not related to cancellation. It has also showed that the effect of sentiment on cancellations behavior appears to be mixed, requiring further analysis. The full project was developed in Python but there was also a comparison with other market solutions as Amazon Web Services, SAS, Google Cloud and Microsoft Azure, in order to find the best Text Mining tool to fit with the company. As expected, Python was elected as the best option.
Singh, P., Y. K. Dwivedi, K. S. Kahlon, R. S. Sawhney, A. A. Alalwan, and Nripendra P. Rana. "Smart monitoring and controlling of government policies using social media and cloud computing." 2019. http://hdl.handle.net/10454/17468.
Full textThe governments, nowadays, throughout the world are increasingly becoming dependent on public opinion regarding the framing and implementation of certain policies for the welfare of the general public. The role of social media is vital to this emerging trend. Traditionally, lack of public participation in various policy making decision used to be a major cause of concern particularly when formulating and evaluating such policies. However, the exponential rise in usage of social media platforms by general public has given the government a wider insight to overcome this long pending dilemma. Cloud-based e-governance is currently being realized due to IT infrastructure availability along with mindset changes of government advisors towards realizing the various policies in a best possible manner. This paper presents a pragmatic approach that combines the capabilities of both cloud computing and social media analytics towards efficient monitoring and controlling of governmental policies through public involvement. The proposed system has provided us some encouraging results, when tested for Goods and Services Tax (GST) implementation by Indian government and established that it can be successfully implemented for efficient policy making and implementation.
Lobo, Afonso José Caldas da Costa. "A DEMOCRATIZAÇÃO DO BUSINESS ANALYTICS: UM EXEMPLO PRÁTICO DE ANÁLISE SENTIMENTAL." Master's thesis, 2019. http://hdl.handle.net/11110/1966.
Full text"A Text Analytic Approach to Study Host Country Nationalist Sentiments and MNE Responses during National Conflicts." 2016. http://repository.lib.cuhk.edu.hk/en/item/cuhk-1292732.
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