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Dissertations / Theses on the topic 'Sentiment Analysis of Marathi Language'

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Published: 3 June 2025
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1

Erogul, Umut. "Sentiment Analysis In Turkish." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610616/index.pdf.

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Sentiment analysis is the automatic classification of a text, trying to determine the attitude of the writer with respect to a specific topic. The attitude may be either their judgment or evaluation, their feelings or the intended emotional communication. The recent increase in the use of review sites and blogs, has made a great amount of subjective data available. Nowadays, it is nearly impossible to manually process all the relevant data available, and as a consequence, the importance given to the automatic classification of unformatted data, has increased. Up to date, all of the research
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Filho, Pedro Paulo Balage. "Aspect extraction in sentiment analysis for portuguese language." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-05122017-140435/.

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Aspect-based sentiment analysis is the field of study which extracts and interpret the sentiment, usually classified as positive or negative, towards some target or aspect in an opinionated text. This doctoral dissertation details an empirical study of techniques and methods for aspect extraction in aspect-based sentiment analysis with the focus on Portuguese. Three different approaches were explored: frequency-based, relation-based and machine learning. In each one, this work shows a comparative study between a Portuguese and an English corpora and the differences found in applying the approa
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Duarte, Eduardo Santos. "Sentiment analysis on twitter for the portuguese language." Master's thesis, Faculdade de Ciências e Tecnologia, 2013. http://hdl.handle.net/10362/11338.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática<br>With the growth and popularity of the internet and more specifically of social networks, users can more easily share their thoughts, insights and experiences with others. Messages shared via social networks provide useful information for several applications, such as monitoring specific targets for sentiment or comparing the public sentiment on several targets, avoiding the traditional marketing research method with the use of surveys to explicitly get the public opinion. To extract information from the large amounts o
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Alotaibi, Saud Saleh. "Sentiment analysis in the Arabic language using machine learning." Thesis, Colorado State University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3720340.

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<p> Sentiment analysis has recently become one of the growing areas of research related to natural language processing and machine learning. Much opinion and sentiment about specific topics are available online, which allows several parties such as customers, companies and even governments, to explore these opinions. The first task is to classify the text in terms of whether or not it expresses opinion or factual information. Polarity classification is the second task, which distinguishes between polarities (positive, negative or neutral) that sentences may carry. The analysis of natural langu
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Nilsson, Ludvig, and Olle Djerf. "How to improve Swedish sentiment polarityclassification using context analysis." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-446382.

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This thesis considers sentiment polarity analysis in Swedish. De-spite being the most widely spoken of the Nordic languages less re-search in sentiment has been conducted in this area compared toneighboring languages. As such this is a largely exploratory projectusing techniques that have shown positive results for other languages.We perform a comparison of techniques applied to a CNN to existingSwedish and multilingual variations of the state of the art BERTmodel. We find that the preprocessing techniques do in fact bene-fit our CNN model, but still do not match the results of fine-tuned BERT
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Li, Wenhui. "Sentiment analysis: Quantitative evaluation of subjective opinions using natural language processing." Thesis, University of Ottawa (Canada), 2008. http://hdl.handle.net/10393/28000.

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Sentiment Analysis consists of recognizing sentiment orientation towards specific subjects within natural language texts. Most research in this area focuses on classifying documents as positive or negative. The purpose of this thesis is to quantitatively evaluate subjective opinions of customer reviews using a five star rating system, which is widely used on on-line review web sites, and to try to make the predicted score as accurate as possible. Firstly, this thesis presents two methods for rating reviews: classifying reviews by supervised learning methods as multi-class classification does,
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Dettori, Emilio. "Sentiment Analysis per la moderazione di una community." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018.

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Questa tesi, dopo aver illustrato i concetti di Machine Learning e Natural Language Processing, descrive il processo di Sentiment Analysis e le sue applicazioni. L'obiettivo del progetto di tesi è stato quello di studiare un sistema di moderazione automatica testuale di una community online, svolto utilizzando le tre tecniche descritte. In particolare, il fine del progetto è quello di effettuare un'analisi lessicale del testo su un corpus creato appositamente, per poi sviluppare algoritmi di Machine Learning in grado di apprendere da esso. Per ogni tecnologia analizzata sono mostrati esempi e
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Olof, Löfving. "Sentiment Analysis of Equity Analyst Research Reports using Convolutional Neural Networks." Thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-388586.

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Natural language processing, a subfield of artificial intelligence and computer science, has recently been of great research interest due to the vast amount of information created on the internet in the modern era. One of the main natural language processing areas concerns sentiment analysis. This is a field that studies the polarity of human natural language and generally tries to categorize it as either positive, negative or neutral. In this thesis, sentiment analysis has been applied to research reports written by equity analysts. The objective has been to investigate if there exist a disti
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Westin, Emil. "Fine-grained sentiment analysis of product reviews in Swedish." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-424266.

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In this study we gather customer reviews from Prisjakt, a Swedish price comparison site, with the goal to study the relationship between review and rating, known as sentiment analysis. The purpose of the study is to evaluate three different supervised machine learning models on a fine-grained dependent variable representing the review rating. For classification, a binary and multinomial model is used with the one-versus-one strategy implemented in the Support Vector Machine, with a linear kernel, evaluated with F1, accuracy, precision and recall scores. We use Support Vector Regression by appr
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Ling, Li, and Simon Larsén. "Sentiment Analysis on Stack Overflow with Respect to Document Type and Programming Language." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229785.

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The sentiment expressed in software engineering (SE) texts has been shown to affect both the productivity and the quality of collaborative work. This is one reason for why sentiment analysis on SE texts has gained attention in research in recent yerars. A large and open resource of SE texts is Stack Overflow (SO). SO is the largest question and answer (Q&amp;A) web site in the Stack Exchange network, and has been the subject for several sentiment analysis studies. It has lately been established that sentiment analyzers trained on social media perform poorly on SE texts, which could challenge t
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CANO, ERION. "Text-based Sentiment Analysis and Music Emotion Recognition." Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2709436.

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Nowadays, with the expansion of social media, large amounts of user-generated texts like tweets, blog posts or product reviews are shared online. Sentiment polarity analysis of such texts has become highly attractive and is utilized in recommender systems, market predictions, business intelligence and more. We also witness deep learning techniques becoming top performers on those types of tasks. There are however several problems that need to be solved for efficient use of deep neural networks on text mining and text polarity analysis. First of all, deep neural networks are data hungry.
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Nepal, Srijan. "Linguistic Approach to Information Extraction and Sentiment Analysis on Twitter." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342544962.

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Tammewar, Aniruddha Uttam. "Deep Emotion Analysis of Personal Narratives." Doctoral thesis, Università degli studi di Trento, 2023. https://hdl.handle.net/11572/364051.

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The automatic analysis of emotions is a well-established area in the natural language processing ( NLP ) research field. It has shown valuable and relevant applications in a wide array of domains such as health and well-being, empathetic conversational agents, author profiling, consumer analysis, and security. Most emotion analysis research till now has focused on sources such as news documents and product reviews. In these cases, the NLP task is the classification into predefined closed-set emotion categories (e.g. happy, sad), or alternatively labels (positive, negative). A deep and fine-gra
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Dahl, Jonas. "Feature Selection for Sentiment Analysis of Swedish News Article Titles." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233534.

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The aim of this study was to elaborate the possibilities of sentiment analyzing Swedish news article titles using machine learning approaches and find how the text is best represented in such conditions. Sentiment analysis has traditionally been conducted by part-of-speech tagging and counting word polarities, which performs well for large domains and in absence of large sets of training data. For narrower domains and previously labeled data, supervised learning can be used. The work of this thesis tested the performance of a convolutional neural network and a Support Vector Machine on differe
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Jakob, Bremer. "Exploring Hybrid Topic Based Sentiment Analysis as Author Identification Method on Swedish Documents." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177893.

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The Swedish national bank has had shifting policies when it comes to publicity and confidentiality concerning publishing of texts within the bank. For some time, texts written by commissioners within the bank were decided to be published anonymously. Later they revoked the confidentiality policy, publishing all documents publicly again. This led to emerged interests in possible shifting attitudes toward topics discussed by the commissioners when writing anonymously versus publicly. On a request, based on the interests, there are ongoing analyses being conducted with the help of language techno
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Htait, Amal. "Sentiment analysis at the service of book search." Electronic Thesis or Diss., Aix-Marseille, 2019. http://www.theses.fr/2019AIXM0260.

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Le Web est en croissance continue, et une quantité énorme de données est générée par les réseaux sociaux, permettant aux utilisateurs d'échanger une grande diversité d'informations. En outre, les textes au sein des réseaux sociaux sont souvent subjectifs. L'exploitation de cette subjectivité présente au sein des textes peut être un facteur important lors d'une recherche d'information. En particulier, cette thèse est réalisée pour répondre aux besoins de la plate-forme Books de Open Edition en matière d'amélioration de la recherche et la recommandation de livres, en plusieurs langues. La platef
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Pérez-Rosas, Verónica. "Exploration of Visual, Acoustic, and Physiological Modalities to Complement Linguistic Representations for Sentiment Analysis." Thesis, University of North Texas, 2014. https://digital.library.unt.edu/ark:/67531/metadc699996/.

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This research is concerned with the identification of sentiment in multimodal content. This is of particular interest given the increasing presence of subjective multimodal content on the web and other sources, which contains a rich and vast source of people's opinions, feelings, and experiences. Despite the need for tools that can identify opinions in the presence of diverse modalities, most of current methods for sentiment analysis are designed for textual data only, and few attempts have been made to address this problem. The dissertation investigates techniques for augmenting linguistic re
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Alsehaimi, Afnan Abdulrahman A. "Sentiment Analysis for E-book Reviews on Amazon to Determine E-book Impact Rank." University of Dayton / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1619109972210567.

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Tempfli, Peter. "Preprocessing method comparison and model tuning for natural language data." Thesis, Högskolan Dalarna, Mikrodataanalys, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:du-34438.

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Twitter and other microblogging services are a valuable source for almost real-time marketing, public opinion and brand-related consumer information mining. As such, collection and analysis of user-generated natural language content is in the focus of research regarding automated sentiment analysis. The most successful approach in the field is supervised machine learning, where the three key problems are data cleaning and transformation, feature generation and model choice and training parameter selection. Papers in recent years thoroughly examined the field and there is a agreement that relat
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Henriksson, Jimmy, and Carl Hultberg. "Public Sentiment on Twitter and Stock Performance : A Study in Natural Language Processing." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259984.

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Since recent years, the use of non-traditional data sources by hedge funds in order to support investment decisions has increased. One of the data sources which has increased most is social media and it has become popular to analyze the public opinion with help of sentiment analysis in order to predict the performance of a company. In order to evaluate the public opinion one need big sets of Twitter data. The Twitter data was collected by streaming the Twitter feed and the stock data was collected from a Bloomberg Terminal. The aim of this study was to examine if there is a correlation between
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Woldemariam, Yonas Demeke. "Natural language processing in cross-media analysis." Licentiate thesis, Umeå universitet, Institutionen för datavetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-147640.

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A cross-media analysis framework is an integrated multi-modal platform where a media resource containing different types of data such as text, images, audio and video is analyzed with metadata extractors, working jointly to contextualize the media resource. It generally provides cross-media analysis and automatic annotation, metadata publication and storage, searches and recommendation services. For on-line content providers, such services allow them to semantically enhance a media resource with the extracted metadata representing the hidden meanings and make it more efficiently searchable. Wi
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Carter, David. "Inferring Aspect-Specific Opinion Structure in Product Reviews." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32177.

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Identifying differing opinions on a given topic as expressed by multiple people (as in a set of written reviews for a given product, for example) presents challenges. Opinions about a particular subject are often nuanced: a person may have both negative and positive opinions about different aspects of the subject of interest, and these aspect-specific opinions can be independent of the overall opinion on the subject. Being able to identify, collect, and count these nuanced opinions in a large set of data offers more insight into the strengths and weaknesses of competing products and services t
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Keshtkar, Fazel. "A Computational Approach to the Analysis and Generation of Emotion in Text." Thèse, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/20137.

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Sentiment analysis is a field of computational linguistics involving identification, extraction, and classification of opinions, sentiments, and emotions expressed in natural language. Sentiment classification algorithms aim to identify whether the author of a text has a positive or a negative opinion about a topic. One of the main indicators which help to detect the opinion are the words used in the texts. Needless to say, the sentiments expressed in the texts also depend on the syntactic structure and the discourse context. Supervised machine learning approaches to sentiment classification
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Larsson, Martin, and Samuel Ljungberg. "Readability: Man and Machine : Using readability metrics to predict results from unsupervised sentiment analysis." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301842.

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Readability metrics assess the ease with which human beings read and understand written texts. With the advent of machine learning techniques that allow computers to also analyse text, this provides an interesting opportunity to investigate whether readability metrics can be used to inform on the ease with which machines understand texts. To that end, the specific machine analysed in this paper uses word embeddings to conduct unsupervised sentiment analysis. This specification minimises the need for labelling and human intervention, thus relying heavily on the machine instead of the human. Acr
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Zeman, Matěj. "Automatizovaná analýza sentimentu." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-193330.

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The goal of my master thesis is to describe the Automated Sentiment Analysis, its methods and Cross-domain problems and to test the already existing model. I have applied this model on the data from the Czech-Slovak film database website CSFD.cz, Czech e-shop MALL.cz and one of the biggest Czech websites about books Databazeknih.cz to contribute to the solution of the Cross-Domain issue by using n-grams and the analytic software RapidMiner.
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Kramer, Stephanie. "Holy day effects on language: How religious geography, individual affiliation and day of the week relate to sentiment and topics on Twitter." Thesis, University of Oregon, 2018. http://hdl.handle.net/1794/23106.

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Religious belief and attendance predict improved well-being at the individual level. Paradoxically, geographic locations with high rates of religious belief and attendance are often those with the differentially high rates of societal instability and suffering. Many of the consequences of religiosity are context-based and vary across time, and holy days are naturally-occurring religious cues that have been shown to influence religiously-relevant attitudes and behaviors. I investigated the degree to which personal religiosity and religious geography (i.e. religious demographics with other locat
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Viegas, Catarina Correia. "Assessing public figures’ reputation through sentiment analysis on twitter using machine learning : creation of a system." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/20993.

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Mestrado em Gestão de Sistemas de Informação<br>Nunca se geraram tantos dados e a um ritmo tão alucinante como atualmente. Vive-se indubitavelmente numa era de Big Data e este termo não passa despercebido, trazendo consigo inúmeros desafios, mas também múltiplas oportunidades. Cerca de 80% dos dados encontra-se de forma desestruturada. Aqui, há um foco especial para o formato de texto, formato esse que para além de comum, agrega um grande potencial. Existem várias aplicações, técnicas e ferramentas associadas à análise de documentos textuais, e esta área surge fortemente ligada ao Processament
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McCarthy, Darcy. "Climate change advocates and deniers? Triangulating methods to investigate the language of left- and right-leaning Twitter users." Thesis, Linguistics, 2023. https://hdl.handle.net/2123/29906.

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This thesis examines left- and right- leaning users on Australian Twitter in an effort to understand the language use of the different parties to online climate change discourse. The data are taken from Australian Twitter users between 2020 and 2022, and split up via a political affiliation metric in order to create two distinct politically-opposed user groups. Three main techniques are used to identify linguistic differences between the two groups: sentiment analysis, multiple correspondence analysis, and keyword analysis. The findings of this thesis are threefold. Firstly, text data collecte
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Pelosi, Serena. "Detecting subjectivity through lexicon-grammar. strategies databases, rules and apps for the italian language." Doctoral thesis, Universita degli studi di Salerno, 2016. http://hdl.handle.net/10556/2208.

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2014 - 2015<br>The present research handles the detection of linguistic phenomena connected to subjectivity, emotions and opinions from a computational point of view. The necessity to quickly monitor huge quantity of semi-structured and unstructured data from the web, poses several challenges to Natural Language Processing, that must provide strategies and tools to analyze their structures from a lexical, syntactical and semantic point of views. The general aim of the Sentiment Analysis, shared with the broader fields of NLP, Data Mining, Information Extraction, etc., is the automatic extrac
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Lamberti, Luca. "TSento: sviluppo di uno strumento per l'analisi del sentiment su risposte aperte nelle indagini di clima aziendale." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.

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Nel seguente elaborato viene introdotto il tema del clima aziendale e viene effettuata una analisi dei problemi legati ai metodi utilizzati nella rilevazione attuale del clima. In seguito viene descritto il processo di sviluppo del prodotto il cui scopo è di risolvere i principali problemi, prima evidenziati, e di fornire maggiori informazioni ai responsabili delle leve che influiscono sulla percezione dell'ambiente di lavoro da parte dei collaboratori. Nella definizione del processo si fa riferimento alle prove empiriche effettuate per determinare quale motore di analisi fosse il migliore, e
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Sommers, Alexander Mitchell. "EXPLORING PSEUDO-TOPIC-MODELING FOR CREATING AUTOMATED DISTANT-ANNOTATION SYSTEMS." OpenSIUC, 2021. https://opensiuc.lib.siu.edu/theses/2862.

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We explore the use a Latent Dirichlet Allocation (LDA) imitating pseudo-topic-model, based on our original relevance metric, as a tool to facilitate distant annotation of short (often one to two sentence or less) documents. Our exploration manifests as annotating tweets for emotions, this being the current use-case of interest to us, but we believe the method could be extended to any multi-class labeling task of documents of similar length. Tweets are gathered via the Twitter API using "track" terms thought likely to capture tweets with a greater chance of exhibiting each emotional class, 3,00
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Pergolini, Diego. "Differentiable Neural Computing: Studio e Sperimentazione nella Cross-Domain Sentiment Classification." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14266/.

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La straordinaria diffusione di piattaforme online attraverso le quali le persone possono esprimere opinioni,come blog, social network,forum, e la conseguente enormità di testo non strutturato generato, ha fatto emergere sempre più interesse verso la Sentiment Classification. Essa, proponendosi di carpire la connotazione, positiva o negativa, di un testo, può assumere un'evidente rilevanza commerciale. Il problema delle soluzioni che sono state proposte in questo ambito è che molto spesso si tratta di tecniche che agiscono con efficacia solo in-domain , cioè addestrando e testando un modello di
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Jäderlund, Maria. "Wed 2.0: improving customer experience with wedding service providers through investigation of the ranking mechanism and sentiment analysis of user feedback on Instagram." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-85220.

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Instagram is one of the main social platforms for business promotion. Millions of potential customers and endless visual marketing opportunities makes Instagram a perfect place to increase online sales. There are many tools and mechanisms to promote brands on Instagram such as paid advertising or using a pre-generated set of popular hashtags. In this regard, the presence and content of users’ comments becomes an important socio-psychological factor in the motivation to buy or use a product or service. The goal of this degree project is to investigate natural language processing techniques appl
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Robinson, Melissa Aubrey. "A Man Needs a Female like a Fish Needs a Lobotomy: The Role of Adjectival Nominalization in Pejorative Meaning." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1157617/.

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This thesis documents the grammatical processes and semantic impact of innovative ways to pejoratively reference individuals through adjectival nominalization. Research on nominalized adjectives suggests that when meanings shift from having one property (1) to becoming a kind with associated properties (2), the noun form often encodes stereotypical attributes: [1] "Her hair is blonde." (hair color); [2] "He married a blonde." (female, sexy, dumb). Likewise, the linguistic phenomenon of genericity refers to classes or kinds and different grammatical structures reflect properties in different w
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Norsten, Theodor. "Exploring the Potential of Twitter Data and Natural Language Processing Techniques to Understand the Usage of Parks in Stockholm." Thesis, KTH, Geoinformatik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278532.

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Traditional methods used to investigate the usage of parks consists of questionnaire which is both a very time- and- resource consuming method. Today more than four billion people daily use some form of social media platform. This has led to the creation of huge amount of data being generated every day through various social media platforms and has created a potential new source for retrieving large amounts of data. This report will investigate a modern approach, using Natural Language Processing on Twitter data to understand how parks in Stockholm being used. Natural Language Processing (NLP)
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Barbato, Massimo-Maria. "Measuring corporate reputation through online social media." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/12434/.

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What is corporate reputation? How can it be measured? These two questions have been widely discussed by academics, without coming to a shared definition or evaluation methodology. Each research gave its own corporate reputation definition, but all the studies agree on one point: corporate reputation is the result of the relationship between a company and its stakeholders. On the stakeholder’s opinion rely most of the corporate rep- utation measurement techniques that have been proposed during the past years, techniques that were criticized. In this work, we have investigated if corporate rep
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Klocok, Andrej. "Analýza recenzí výrobků." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-417231.

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Online store customers generate vast amounts of product and service information through reviews, which are an important source of feedback. This thesis deals with the creation of a system for the analysis of product and shop reviews in the czech language. It describes the current methods of sentiment analysis and builds on current solutions. The resulting system implements automatic data download and their indexing, subsequently sentiment analysis together with text summary in the form of clustering of similar sentences based on vector representation of the text. A graphical user interface in
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Cunningham-Nelson, Samuel Kayne. "Enhancing student conceptual understanding and learning experience through automated textual analysis." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/134145/1/Samuel_Cunningham-Nelson_Thesis.pdf.

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Supporting students to develop a strong foundation for thorough understanding, and assisting educators in teaching effectively, both require the utilization of meaningful feedback. The contributions presented in this thesis aimed to provide instantaneous, and individualised feedback for both students and educators through the use of text analysis. The methodologies and models described are all automated, therefore once implemented can provide feedback routinely and recurrently. These solutions facilitate both learning and teaching for students and educators, respectively, helping to close the
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Padilla, López Rebeca. "Word Frequency as a Predictor of Word Intensity." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-325301.

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In this thesis we explore the intensity of adjectives and how it can be predicted by different word features. We investigate how to accurately determine intensity between synonymous adjectives. For this, we look at features such as word frequency, number of senses and syllable length. Our study is inspired by life satisfaction and happiness surveys and the possibility that differences in intensity in the translation of the adjectives used for the questionnaires could explain the high degree of satisfaction that some countries show. We base our hypothesis on the theories of grammaticalization a
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Fiati-Kumasenu, Albert. "Extracting Customer Sentiments from Email Support Tickets : A case for email support ticket prioritisation." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18853.

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Background Daily, companies generate enormous amounts of customer support tickets which are grouped and placed in specialised queues, based on some characteristics, from where they are resolved by the customer support personnel (CSP) on a first-in-first-out basis. Given that these tickets require different levels of urgency, a logical next step to improving the effectiveness of the CSPs is to prioritise the tickets based on business policies. Among the several heuristics that can be used in prioritising tickets is sentiment polarity. Objectives This study investigates how machine learning meth
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Björner, Amanda. "Natural Language Processing techniques for feedback on text improvement : A qualitative study on press releases." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301303.

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Press releases play a key role in today’s news production by being public statements of newsworthy content that function as a pre-formulation of news. Press releases originate from a wide range of actors, and a common goal is for them to reach a high societal impact. This thesis examines how Natural Language Processing (NLP) techniques can be successful in giving feedback to press release authors that help enhance the content and quality of their texts. This could, in turn, contribute to increased impact. To examine this, the research question is divided into two parts. The first part examines
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Guardati, Simone. "Realizzazione di una infrastruttura di Opinion Mining per commenti testuali." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.

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Milioni di commenti ogni giorno vengono scritti ed aggiunti su internet da migliaia di utenti, essi riguardano ristoranti, hotel, acquisti, luoghi da visitare e molto altro. Quotidianamente moltissime persone fano affidamento su tali opinioni, ad esempio preferendo l’acquisto di un prodotto rispetto ad un altro su un sito di e-commerce, rendendo così il valore di questi dati molto elevato ed una loro analisi un processo molto importante da effettuare. Estrarre le informazioni di interesse da essi è un procedimento difficilmente eseguibile da operatori umani data la loro enorme quantità, di con
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Konstantinova, Natalia. "Knowledge acquisition from user reviews for interactive question answering." Thesis, University of Wolverhampton, 2013. http://hdl.handle.net/2436/297401.

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Nowadays, the effective management of information is extremely important for all spheres of our lives and applications such as search engines and question answering systems help users to find the information that they need. However, even when assisted by these various applications, people sometimes struggle to find what they want. For example, when choosing a product customers can be confused by the need to consider many features before they can reach a decision. Interactive question answering (IQA) systems can help customers in this process, by answering questions about products and initiatin
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Pecore, Stefania. "Analyse des sentiments et des émotions de commentaires complexes en langue française." Thesis, Lorient, 2019. http://www.theses.fr/2019LORIS522/document.

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Les définitions des mots « sentiment », « opinion » et « émotion » sont toujours très vagues comme l’atteste aussi le dictionnaire qui semble expliquer un mot en utilisant le deux autres. Tout le monde est affecté par les opinions : les entreprises pour vendre les produits, les gens pour les acheter et, plus en général, pour prendre des décisions, les chercheurs en intelligence artificielle pour comprendre la nature de l’être humain. Aujourd’hui on a une quantité d’information disponible jamais vue avant, mais qui résulte peu accessible. Les mégadonnées (en anglais « big data ») ne sont pas or
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Giménez, Fayos María Teresa. "Natural Language Processing using Deep Learning in Social Media." Doctoral thesis, Universitat Politècnica de València, 2021. http://hdl.handle.net/10251/172164.

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[ES] En los últimos años, los modelos de aprendizaje automático profundo (AP) han revolucionado los sistemas de procesamiento de lenguaje natural (PLN). Hemos sido testigos de un avance formidable en las capacidades de estos sistemas y actualmente podemos encontrar sistemas que integran modelos PLN de manera ubicua. Algunos ejemplos de estos modelos con los que interaccionamos a diario incluyen modelos que determinan la intención de la persona que escribió un texto, el sentimiento que pretende comunicar un tweet o nuestra ideología política a partir de lo que compartimos en redes sociales.
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Povoda, Lukáš. "Dolovanie znalostí z textových dát použitím metód umelej inteligencie." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2018. http://www.nusl.cz/ntk/nusl-391304.

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This work deals with the problem of text mining which is becoming more popular due to exponential growth of the data in electronic form. The work explores contemporary methods and their improvement using optimization methods, as well as the problem of text data understanding in general. The work addresses the problem in three ways: using traditional methods and their optimizations, using Big Data in train phase and abstraction through the minimization of language-dependent parts, and introduction of the new method based on the deep learning which is closer to how human reads and understands te
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Vázquez, Suárez Silvia. "Pattern-based automatic induction of domain adapted resources for social media analysis." Doctoral thesis, Universitat Pompeu Fabra, 2016. http://hdl.handle.net/10803/350801.

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In this dissertation, we analyze different aspects of the language used in texts published along different social media, and we propose a set of methods for the automatic extraction of polar adjectives as well as for the automatic classification of these texts. First of all, we propose a new classification of polar adjectives according to their lexical features, based on a case study. Secondly, we implement a new domain adaptable system for the automatic extraction of polar adjectives (along with their polarity values), reducing the use of external language resources. Finally, we propos
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Igboayaka, Jane-Vivian Chinelo Ezinne. "Using Social Media Networks for Measuring Consumer Confidence: Problems, Issues and Prospects." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32341.

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This research examines the confluence of consumers’ use of social media to share information with the ever-present need for innovative research that yields insight into consumers’ economic decisions. Social media networks have become ubiquitous in the new millennium. These networks, including, among others: Facebook, Twitter, Blog, and Reddit, are brimming with conversations on an expansive array of topics between people, private and public organizations, governments and global institutions. Preliminary findings from initial research confirms the existence of online conversations and posts re
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Demmelmaier, Gustav, and Carl Westerberg. "Data Segmentation Using NLP: Gender and Age." Thesis, Uppsala universitet, Avdelningen för datalogi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-434622.

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Natural language processing (NLP) opens the possibilities for a computer to read, decipher, and interpret human languages to eventually use it in ways that enable yet further understanding of the interaction and communication between the human and the computer. When appropriate data is available, NLP makes it possible to determine not only the sentiment information of a text but also information about the author behind an online post. Previously conducted studies show aspects of NLP potentially going deeper into the subjective information, enabling author classification from text data. This th
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Glant, Oliver. "Attitydanalys av svenska produktomdömen – behövs språkspecifika verktyg?" Thesis, Stockholms universitet, Institutionen för lingvistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-157094.

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Sentiment analysis of Swedish data is often performed using English tools and machine. This thesis compares using a neural network trained on Swedish data with a corresponding one trained on English data. Two datasets were used: approximately 200,000 non-neutral Swedish reviews from the company Prisjakt Sverige AB, one of the largest annotated datasets used for Swedish sentiment analysis, and 1,000,000 non-neutral English reviews from Amazon.com. Both networks were evaluated on 11,638 randomly selected reviews, in Swedish and in English machine translation. The test set had the same overrepres
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