Sentiment analysis of Movie reviews and Blog posts

Singh, Vivek Kumar; Piryani, Rajesh; Uddin, Ashraf; Waila, P.

doi:10.1109/iadcc.2013.6514345

Cited by 49 publications

(19 citation statements)

References 7 publications

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“…A feature based sentiment analysis for product reviews is provided in [11].This method focuses on combined use of coreference resolution, domain specific aspect dictionary, SentiWordNet, linguistic rules, adjectives, verbs, adverb adjective combinations and adverb verb combinations together for sentiment analysis of features. [12]proposed an aspect oriented approach that analyses the textual reviews of a movie and assigns a sentiment label. The scores on each aspect from multiple ©IJRASET (UGC Approved Journal): All Rights are Reserved reviews are then aggregated and a net sentiment profile of the movie is generated based on certain parameters.…”

Section: Sentiment Analysis Toolsmentioning

confidence: 99%

Sentiment Analysis Tools and Techniques: A Comprehensive Survey

Barretto¹

2017

IJRASET

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Data analysis refers to a process of inspecting and transforming data in order to derive some useful information. The objective of this process is to discover interesting patterns that can be used to derive important conclusions in areas like business, science, and social science domains. Semantic analysis plays a very important role in decision making process. Due to increase in web technologies a large amount of data gets generated. In order to extract important data from this, various data mining techniques have been proposed in recent years. Many researchers have focused on finding some interesting patterns out of this data using semantic analysis techniques. These techniques basically deal with determining the contextual polarity with reference to a specific domain. The paper presents a comprehensive survey about various techniques and tools used for sentiment analysis with some newer approaches like sentiment analysis using LDA. We present a comprehensive survey of latest sentiment analysis techniques along with some comparison results.

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Section: Sentiment Analysis Toolsmentioning

confidence: 99%

Sentiment Analysis Tools and Techniques: A Comprehensive Survey

Barretto¹

2017

IJRASET

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“…Moreover, understanding the usability issues faced by laptop customers allow the manufacturer an opportunity to further ameliorate their laptops. However, the quintillion bytes of data generated per day consisting of user feedback cannot be manually read and analyzed by an individual or an organization, for gauging public opinion [3,4]. Sentiment analysis is an automated process of computationally understanding and classifying subjective information from source materials such as reviews on e-commerce websites, and posts/comments on social media platforms.…”

Section: Introductionmentioning

confidence: 99%

A hybrid Persian sentiment analysis framework: Integrating dependency grammar based rules and deep neural networks

et al. 2020

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Social media hold valuable, vast and unstructured information on public opinion that can be utilized to improve products and services. The automatic analysis of such data, however, requires a deep understanding of natural language.Current sentiment analysis approaches are mainly based on word co-occurrence frequencies, which are inadequate in most practical cases. In this work, we propose a novel hybrid framework for concept-level sentiment analysis in Persian language, that integrates linguistic rules and deep learning to optimize polarity detection. When a pattern is triggered, the framework allows sentiments to flow from words to concepts based on symbolic dependency relations. When no pattern is triggered, the framework switches to its subsymbolic counterpart and leverages deep neural networks (DNN) to perform the classification. The proposed framework outperforms state-of-the-art approaches (including support vector machine, and logistic regression) and DNN classifiers (long short-term memory, and Convolutional Neural Networks) with a margin of 10-15% and 3-4% respectively, using benchmark Persian product and hotel reviews corpora.

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“…Many studies conducted experiments on sentiment analysis with the dataset of online movie reviews [3,11,32,33]. Some researchers identified the important aspects of products by performing sentiment analysis for online consumer reviews [5,20].…”

Section: Introductionmentioning

confidence: 99%

The application and comparison of web services for sentiment analysis in tourism

Gao

Jiang

2015

2015 12th International Conference on Service Systems and Service Management (ICSSSM)

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The popularity of social computing and sentiment analysis has attracted an increasing attention of tourism industry and academia. The sentiment analysis of residents' and tourists' plays an important role to the development of tourism. It aims to identify and analyze opinions and emotions contained in reviews which are expressed by residents or tourists. Although it's a challenging task, many companies and research institutes are developing web services to provide public-access and cost-effective solutions to the problem. However, to the best of our knowledge, there are very few studies to apply and compare these web services in tourism. Therefore, in this work we make an initial attempt to explore a set of three web services and compare their sentiment analysis capabilities using the well-known TripAdvisor data collection. Experiment results lead to some interesting conclusions.

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Sentiment analysis of Movie reviews and Blog posts

Cited by 49 publications

References 7 publications

Sentiment Analysis Tools and Techniques: A Comprehensive Survey

Sentiment Analysis Tools and Techniques: A Comprehensive Survey

A hybrid Persian sentiment analysis framework: Integrating dependency grammar based rules and deep neural networks

The application and comparison of web services for sentiment analysis in tourism

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