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sentiment-analysis
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Extraction and Analysis of Product Aspects of Online Stores Based on Customers' Reviews Using Machine Learning Techniques
, M.Sc. Thesis Sharif University of Technology ; Habibi, Moslem (Supervisor) ; Fazli, Mohammad Amin (Supervisor)
Abstract
Today, with the popularity of online shopping, many business owners are interested in launching online stores. Recording opinions and using the opinions of customers and buyers of products provides the possibility of listening to the opinions of customers in the design and improvement of products. On the other hand, other users and those who intend to buy a specific product, after paying attention to the features and aspects of the product they want, refer to the section of customer views and opinions. The user also reads these comments among thousands of different sentences and words written with different opinions and suggests; It gets confusing and many users won't be able to make the...
Creating sentiment lexicon for sentiment analysis in Urdu: The case of a resource-poor language
, Article Expert Systems ; Volume 36, Issue 3 , 2019 ; 02664720 (ISSN) ; Sattar, A ; Khan, A ; Ali, A ; Masud Kundi, F ; Ahmad, S ; Sharif University of Technology
Blackwell Publishing Ltd
2019
Abstract
The sentiment analysis (SA) applications are becoming popular among the individuals and organizations for gathering and analysing user's sentiments about products, services, policies, and current affairs. Due to the availability of a wide range of English lexical resources, such as part-of-speech taggers, parsers, and polarity lexicons, development of sophisticated SA applications for the English language has attracted many researchers. Although there have been efforts for creating polarity lexicons in non-English languages such as Urdu, they suffer from many deficiencies, such as lack of publically available sentiment lexicons with a proper scoring mechanism of opinion words and modifiers....
How will your tweet be received? predicting the sentiment polarity of tweet replies
, Article 15th IEEE International Conference on Semantic Computing, ICSC 2021, 27 January 2021 through 29 January 2021 ; 2021 , Pages 370-373 ; 9781728188997 (ISBN) ; Monajem, M ; Christlein, V ; Heinrich, P ; Nicolaou, A ; Naderi Boldaji, H ; Lotfinia, M ; Evert, S ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2021
Abstract
Twitter sentiment analysis, which often focuses on predicting the polarity of tweets, has attracted increasing attention over the last years, in particular with the rise of deep learning (DL). In this paper, we propose a new task: predicting the predominant sentiment among (first-order) replies to a given tweet. Therefore, we created RETwEET, a large dataset of tweets and replies manually annotated with sentiment labels. As a strong baseline, we propose a two-stage DL-based method: first, we create automatically labeled training data by applying a standard sentiment classifier to tweet replies and aggregating its predictions for each original tweet; our rationale is that individual errors...
Enhancing Opinion Mining in Social Networks using Graph-based Analysis
, M.Sc. Thesis Sharif University of Technology ; Moghadasi, Reza (Supervisor)
Abstract
In the past, opinion polls have generally been conducted using statistical techniques and the comments of those samples, which, in addition to its various challenges, require much power and cost per poll. Today, due to the high penetration rate of social networks in society, a very large fraction of people discuss such issues in terms of their opinions and preferences in these networks, and hence, these networks can be a valuable source of information to get the opinions of people in a short time, and by lower cost.The purpose of this thesis is to enhancing the results of the surveys which have already performed using various methods of text processing in social networks by using the graph...
Aspect-based Opinion Mining for Product Reviews
,
M.Sc. Thesis
Sharif University of Technology
;
Beigy, Hamid
(Supervisor)
Abstract
Other people’s opinions are important piece of information for making informed decisions. With the expansion of using internet, today the web has become an excellent source of user’s viewpoints in different domains. However, in one hand, the growing volume of opinionated text and on the other hand, complexity caused by contrast in user opinion, makes it almost impossible to read all of these reviews and make an informed decision. These needs, have inspired a new line of research on mining user reviews, which is called “opinion mining”. One of the most challenging sub-problems of opinion mining, is “aspect-based opinion mining”. The goal of aspect-based opinion mining is to extract different...
Investigation and Analysis in Social Media Data and Cryptocurrency Bubble Fluctuations
, M.Sc. Thesis Sharif University of Technology ; Fatahi Valilai, Omid (Supervisor) ; Haji, Alireza (Supervisor) ; Beigi, Hamid (Co-Supervisor)
Abstract
Behavioral economics demonstrates that the sentiment can affect the behaviors and financial decisions of people. Can this be generalized to societies? For instance, is it possible for societies to experience emotions that will change their ways of decision making? This thesis attempts to perform an experiment addressing these questions. Bitcoin has been facing a transient phase of price volatilities. Many articles believe that bitcoin does not have an inherent value and is only derived by factors like the perception and acceptance of it and the sentiments among the investors. Digital currencies provide the unique possibility of measuring socioeconomic signals using digital traces.The...
Cryptocurrency Price Prediction based on Text Analysis
, M.Sc. Thesis Sharif University of Technology ; Akhavan Niaki, Taghi (Supervisor)
Abstract
Investors' sentiment toward a coin is very vital in cryptocurrencies' markets. If traders do not invest in a coin, its price will decline; therefore, it is essential for investors to take others' sentiment into account when they want to buy or sell a coin. Text mining on social media is one technique that can help traders understand others' opinions about the coin they are trading. Hence, in this research, we try to predict the top three cryptocurrencies, Bitcoin, Etheruem, and Litecoin, price movement for the next day based on Twitter posts and News title using text mining. In this research, we found out that considering all tweets can reduce our model's accuracy, and for better accuracy,...
Controlling Emotional State by Environmental Modification
, M.Sc. Thesis Sharif University of Technology ; Bagheri Shouraki, Saeed (Supervisor)
Abstract
With the development of artificial intelligence as well as robotics, affective computing which is about recognizing human emotions by machines and creating artificial emotions in them in order to create a proper social reaction is becoming an important topic. Most of the research in this field has been focused on recognizing and detecting human emotions. In this study, assuming a proper understanding of emotions by artificial intelligence models, an attempt has been made to better clarify the emotional space. In more detail, the goal is to examine the changes in the human emotional state in order to gain better control of his behavior. In this study, by analyzing the feelings of users and...
How People's Sentiment and Attention Affect the Return of Bitcoin?
, M.Sc. Thesis Sharif University of Technology ; Aslani, Shirin (Supervisor) ; Talebian, Masoud (Co-Supervisor)
Abstract
With the huge growth of cryptocurrencies in recent years, the attention of investors has been drawn to predict and invest in it. Because of the high volatility of this market, which includes a large share of Bitcoin, there is a need for good forecasting in it. Although past studies have been able to accurately predict the price of Bitcoin using fundamental variables and variables related to the blockchain network, less attention has been paid to the use of variables related to investor sentiments in this market. In this research, variables widely used in the literature that show the emotions and attention of investors, such as sentiment analysis of Twitter texts, Google search index,...
Cross-Lingual Sentiment Analysis of Persian Text Using Deep Learning
, M.Sc. Thesis Sharif University of Technology ; Ghasem-Sani, Gholamreza (Supervisor)
Abstract
One of the subfields of natural language processing is sentiment analysis. Generally, sentiment analysis, analyzes the positivity, or negativity of an opinion expressed in a sentence or document. Because each person's opinions have a huge impact on the decisions of other people and businesses, automatic analysis of texts has a particular importance; on which, extensive researches have been conducted in recent years. One of the common problems in sentiment analysis of some languages, including Persian, is the lack of proper resources in them. Cross-lingual sentiment analysis is one solution to this problem. In these methods, the goal is, through using the rich resources available in a source...
Election vote share prediction using a sentiment-based fusion of Twitter data with Google trends and online polls
, Article 6th International Conference on Data Science, Technology and Applications, DATA 2017, 24 July 2017 through 26 July 2017 ; 2017 , Pages 363-370 ; 9789897582554 (ISBN) ; Modirshanechi, A ; Aghajan, H. K ; Institute for Systems and Technologies of Information, Control and Communication (INSTICC) ; Sharif University of Technology
SciTePress
2017
Abstract
It is common to use online social content for analyzing political events. Twitter-based data by itself is not necessarily a representative sample of the society due to non-uniform participation. This fact should be noticed when predicting real-world events from social media trends. Moreover, each tweet may bare a positive or negative sentiment towards the subject, which needs to be taken into account. By gathering a large dataset of more than 370,000 tweets on 2016 US Elections and carefully validating the resulting key trends against Google Trends, a legitimate dataset is created. A Gaussian process regression model is used to predict the election outcome; we bring in the novel idea of...
Recommending Aspect Changes for Mobile Apps Via Mining Users’ Reviews
, M.Sc. Thesis Sharif University of Technology ; Heydarnoori, Abbas (Supervisor)
Abstract
Dental implants should be biocompatible. This ability cause bone growth beside implant and increases stability of implant. Manufactoring method and materials used in implants are main parameters affectig biocompatibility of implants. Fabrication of functionally graded structures is a novel method to increase biocompatibility. Stress shielding is one of the main causes of failures in current dental implants. This phenomenon takes place due to different young modulus of dental implants and host bone. Pouros structures remedial this problem and implant’s young modulus comes closer to host bone. The aim of this project is to study feasibily of fabrication of functionally graded titanium dental...
Persian Aspect-based Sentiment Analysis using Unsupervised Learning Methods
, M.Sc. Thesis Sharif University of Technology ; Ghasem-Sani, Gholamreza (Supervisor)
Abstract
Sentiment analysis, is a subfield of natural language processing that aims at opinion mining to analyze thoughts, orientation and evaluation of users within some texts. Different organizations in multiple social domains, use this approach as a tool to asses their strengths and shortcomings. In sentiment analysis, the goal is to use machine learning techniques with the purpose of specifying users’ positive or negative orientation about a product or merchandise. The solution to this problem includes two main steps: extracting aspects and determining users’ positive or negative sentiments in respect to the aspects. Two main challenges of sentiment analysis in Farsi, are lack of comprehensive...
Analysing Purchase Satisfaction Using Opinion Mining
, M.Sc. Thesis Sharif University of Technology ; Beigy, Hamid (Supervisor)
Abstract
Opinions and experiences of others give us valuable information in making decisions. Recently, with the expansion of using social networks and websites, people can easily share their opinions about miscellaneous things. This huge amount of information cannot be analyzed by individuals, so a system that automatically analyzes opinions is needed. This need invokes new field of research that is called opinion mining. User’s viewpoints could change during the time, and this is an important issue for companies. One of the most challenging sub-problems of opinion mining is model-based opinion mining, which aims to model the generation of words by modeling their probabilities. In this thesis, we...
Persian Aspect-based Sentiment Analysis Using Learning Methods
, M.Sc. Thesis Sharif University of Technology ; Ghassem Sani, Gholamreza (Supervisor)
Abstract
As digital content grows rapidly due to the internet, user reviews about different topics such as product quality can be used as a rich source to check and analyze product quality and performance. Automatic methods are being widely used to extract these information because of the massive amount of available resources. Sentiment analysis is one of the important fields in natural language processing, which uses a combination of learning and rule-based methods to extract subjective information out of documents. Aspect based sentiment analysis deals with sentiment analysis based on each aspect of the product. It consists of two main steps: first, aspects should be extracted from the reviews and...
News-based Stock Forecasting Using Text Mining Methods
, M.Sc. Thesis Sharif University of Technology ; Rafiee, Majid (Supervisor)
Abstract
Predicting the trend of stock prices is always one of the concerns that stock market analysts and investors face with, which plays a critical role in maximizing the profit from investing in stocks. Past stock price charts, raw material prices, the value of the company's assets, the impact of global markets, the company's products, the organization's development plans, and the same other factors influencing the stock price. News reports are an important source of information for people. Recently, a lot of research has been done to examine the impact of news on stock price trends. This research has two research phases. In the first phase, a text mining method is presented which is using...
Classifying Users’ Reviews to Respond in App Stores
, M.Sc. Thesis Sharif University of Technology ; Heydarnoori, Abbas (Supervisor)
Abstract
In recent years, the number of applications in app stores such as Google Play has increased dramatically. In Google Play, people can write a review and give a rate to each application. Each review contains a lot of notable information such as ‘feature request’ which helps with software maintenance. Also, the user rate is a sign of user satisfaction or dissatisfaction. Users can change their reviews and rate anytime they want. The previous studies show that total rating affects the success of apps and the total number of downloads. They also found that a lot of users take the rating as one of the important factors while downloading the app and they usually don’t download the apps which have...
The Effect of Investors' Sentiment on Price to Earning Ratio of the Tehran Stock Exchange
, M.Sc. Thesis Sharif University of Technology ; Barakchian, Mahdi (Supervisor)
Abstract
Price to earnings ratio is one of the most used ratios in financial markets for valuation of firms in the Iran and world. In present research for analysis of this ratio,investors’ sentiment alongside fundamental factors affecting price to earnings ratio has been investigated. Fundamental factors affecting this ratio are selected based on prior research and economics theory; these factors are, dividend ratio, growth,risk and inflation. For the analysis of investors’ sentiment, eight proxies related to sentimental behavior have been utilized; among them, four are introduced and used for the first time in this research. Implementing these eight sentimental proxies, a variable measuring...
Analysis of the Paris Agreement Discussion on Twitter
, M.Sc. Thesis Sharif University of Technology ; Mirnezami, Reza (Supervisor)
Abstract
With millions of users worldwide, Twitter has become a tool for reflecting the ideas and concerns of society and social movements in various fields, such as environmental concerns. Since the introduction of Twitter in October 2006, this social network has attracted many users from various fields including academia, politics, and business. Despite the limitations of Twitter users' distributions in terms of age and geography, the analysis of these discourses is important because of the real-time sharing of opinions. In this study, the number of 195,917 tweets with the hashtag Paris agreement, paris accord from 2015 to 2021 have been studied by the snscrape library in Python software with the...
Stock Market Trend Prediction Using Sentiment Analysis
, M.Sc. Thesis Sharif University of Technology ; Habibi, Jafar (Supervisor)
Abstract
Stock price prediction is a serious challenge for investors and corporate stockholders to forecast the daily behavior of the stock market, which helps them to invest with more confidence by taking risks and fluctuations into consideration. Stock price prediction is a difficult task, since it is very depending on the demand of the stock, and there is no certain variable that can precisely predict the demand of one stock each day.During the past few decades, time series analysis has become one popular method for solving the stock forecasting problem. However, depending only on the stock index series makes the performance of the forecast not good enough, because many external factors which may...