Sentiment analysis, also called as opinion mining, is the field of study that analyzes people’s opinions, sentiments, evaluations, appraisals, attitudes and emotion towards entities such as products, services or organizations, individuals, issues, topics and their attributes. Sentiment analysis and opinion mining mainly focuses on opinions which express or imply positive, negative or neutral sentiments. Due to the big diversity and size of social media there is a need of automated and real time opinion extraction and mining. Mining online opinion is a form of sentiment analysis that is treated as a difficult text classification task. My thesis contain the identification of accurately classifying the sentiment in text from micro blogs. This addresses the problem by retrieving opinions, performing processing on the data and analyzing the data using machine learning techniques to classify them by sentiment as positive, negative or neutral. I proposed sentimental natural language processing method for processing the text and use various machine learning algorithms and feature selection methods to determine the best approach. The approaches towards sentiment analysis are machine learning based methods, lexicon based methods and linguistic analysis. I proposed sentimental natural language processing Model for processing text to remove irrelevant features that do not affect its orientation. Sentimental natural language processing model carries opinions in natural language process as well as unstructured reviews with pointers, punctuations, emotions, repeated words, symbols, WH questions, URL’s are preprocessed to extract relevant features while sanitizing inputs. Sentimental natural language processing measures the importance of feature... ... middle of paper ... ... applied on different Domain data sets and sub level data sets. The data sets are applied on Maximum entropy, Support Vector Machine Method, Multinomial naïve bayes algorithms, I got 60-70% of accuracy. The above is also applied for the Unigrams of Maximum entropy, Support Vector Machine Method, Multinomial naïve bayes algorithms achieved an accuracy of 65-75%. Applied the same data on proposed lexicon Based Semantic Orientation Analysis Algorithm, we received better accuracy of 85%. In subjective Feature Relation Networks Chi-square model using n-grams, POS tagging by applying linguistic rules performed with highest accuracy of 80% to 93% significantly better than traditional naïve bayes with unigram model. The after applying proposed model on different sets the results are validated with test data and proved our methods are more accurate than the other methods.
When a person is shopping they typically are drawn to something eye catching that is either in or on the storefront. Some storefronts appeal to a very specific customer group whereas others are very general. One storefront that does a good job of pulling the attention of a fairly specific customer group is H&M. The front of this store is very modern, with clean lines that make it appear very sleek and elegant. Something else that this store does that helps them is that almost the entire storefront is made of huge floor to ceiling windows which not only go along to the sleek, modern design but it also allows the customers to see completely into the store. The front of this store helps them to attract the customer group that they are targeting because it gives off a very professional and sophisticated vibe that goes with the type of people that shop there. The floor to ceiling glass windows also help the store attract customers because it
Introduction Teachers have become gateway keepers to providing education to students. Over the span of several years, teachers have been criticized for being unprepared, unable to adapt to different learning styles, and are increasing the number of students who aren’t learning. With this achievement gap increasing, it brings up the idea of what the education system is doing wrong and what improvements it needs to make. The education system needs to be redesigned to strengthen its curriculum, it’s connection to both practice and theory, and the idea of a powerful educator. The first aspect of this memo contains an interview with Diana Regalado De Santiago, a math teacher in the Socorro Independent School District for the past six years.
A rhetoric analysis can be defined as the breakdown of components used to make a persuasive argument or judgment on a particular subject or topic. The ability to make a conclusion or decision on a given thought or idea in a moment of seconds is a result of rhetorical analysis. “Because media rhetoric surrounds us, it is important to understand how rhetoric works. If we refuse to stop and think about how and why it persuades us, we can become mindless consumers who buy into arguments about what makes us value ourselves and what makes us happy”. In Carroll’s essay “Backpacks Vs. Briefcases: Steps toward Rhetorical Analysis”, she discusses the nature of rhetorical analysis, how it affects our everyday lives and explains the role context plays.
John Marsh, Ph.D., shares his epiphany, that his sharing the popular belief that higher education was the answer to bringing about economic equality and curing poverty, was in fact wrong; in this short selection, “Why Education Is Not an Economic Panacea”, taken from his book, “Class Dismissed: Why We Cannot Teach or Learn Our Way Out of Inequality”. Marsh had felt that gaining a higher education himself worked to bring him to a level of economic equality, so, it should work the same way for everyone else. His change of heart comes after perhaps stepping down from the pedestal that many, with lots of letters after their name, sit on, or are put upon by others, and witnessing first-hand the dismal rates of graduation of students in the single course he teaches for The Odyssey Program. Serving as good Public Relations for the University of Illinois at Urbana-Champaign, the program’s purpose was two-fold; it was to provide, at no cost, college level course(s) for low-income adults and look good for the University. In this excerpt, Marsh’s narrow vision seems to have opened up somewhat, however, it does not demonstrate that his visual field widened enough to see that there is much, much more than simply economics or education that is at play in determining where people end up in the spectrum of being considered successful in the United States. (Marsh 914)
Rhetoric . A word many believe withholds a negative connotation in reference to politics, yet little did do they know, such a small-scale word has numerous definitions. Rhetoric , wWhen used in a different context, it can mean many different thingscan have many different meanings. As mentioned abovementioned, it is known to have a negativebad implication, reason being, that candidates use certain persuading techniques towards voters in order to bash their opponents. That way, they can gain votes for their own party, and convince the voters that other candidates are doing things the wrong way and gain votes for their own party. I personally perceive rhetoric as an act of communication that demands a response. as an act
Director Steven Spielberg and auther Markus Zusak, in their intriguing production, movie Saving Private Ryan and book The Book Thief, both taking place during World War II. However , in Saving Private Ryan Spielberg focus on a lot of complications that occur during war , but guilt was one difficulty that stood out to me. Zusak, on the other hand , showas that having courage during war can be a advantage and also an disadvantage depending on the situation. Both director and author grabed the audience attention with emotional and logical appeal.
...e predictive qualities, used in the box office revenues study, S Asur, BA Huberman (2010), is a definite sign that there is potential in analysing the mass of data within social media, and use it to predict future outcomes. There is the idealism that if everyone invests in the same asset or security looking for positive returns, it is a self-fulfilling prophecy in that the price will increase. In the same respect if everyone is sharing and spreading the information repeatedly. I believe we definitely could use the data that can be mined from Twitter, for predictive measures. Even though several of the studies looked at, analyse the data after the events, if further analysis was to happen, potentially looking to extrapolate the relationships, and using differentiation, to find the reactions as the sentiments change on Twitter; it could be used in a predictive manner.
Social media is becoming an essential part of life as social media sites and applications are growing in use among everyday life. [1] It is a marketing tool that allows companies to reach out to the customers and be able to connect with them and organizations are able to trust social media sites as they put information about their companies onto these media sites. [2] Tools such as Facebook, YouTube, Twitter, LinkedIn and other social sites are the main content based which allows the interactive web to interact with the users who participate, they can comment and create content in terms of communicating with mutual users and the public. [3] This has resulted in information being easily shared, searched, promoted, disputed and be created. [4]
Social media is an imperative public relations tool for companies to utilize in their business practices. Social media cannot be regulated so anyone can say what they please about the company, whether it is good, bad or ugly. Social media is developing rapidly and there are new platforms
Social networking has increasingly had a huge impact on society. Technology has opened the door to a vast amount of information and to the ability to relay that information to practically anybody at anytime and anywhere. People are constantly checking their email, updating their status on Facebook, sending tweets on Twitter, instant messaging, and texting. The debate of whether social networking actually connects us or keeps us apart is a continuous one. In the case of Steven Pinker, his essay “Mind over Mass Media” argues that media technologies have a positive effect on mental development. In contrast, Sherry Turkle’s essay “Connectivity and Its Discontents” asserts that technology has a negative effect on interpersonal relationships. Although Pinker makes many excellent points on how technology is improving intelligence and Turkle provides exceptional ideas of how technology is damaging to relationships, neither Pinker nor Turkle provides the best answer to this question due to their lack of credibility and inclusion of logical fallacies. Instead, we should use the Internet to its full potential, while being aware of the risks and dangers that come with social networking.
Introduction I want to thank you and congratulate you for downloading the book How to Find a Profitable Blog Topic Idea: How to Blog and Generate Profitable Blog Topic Ideas. This book contains proven steps and strategies on how to become a truly a professional blog writer. It will teach you how to choose the most important aspect of your blog, which is the blog’s theme or topic! Here is an inescapable fact: you will need to know how to choose the proper topic for your blog if you want to get enough followers for it to become profitable in the future.
The field of Computational Linguistics is relatively new; however, it contains several sub-areas reflecting practical applications in the field. Machine (or Automatic) Translation (MT) is one of the main components of Computational Linguistics (CL). It can be considered as an independent subject because people who work in this domain are not necessarily experts in the other domains of CL. However, what connects them is the fact that all of these subjects use computers as a tool to deal with human language. Therefore, some people call it Natural Language Processing (NLP). This paper tries to highlight MT as an essential sub-area of CL. The types and approaches of MT will be considered, and limitations discussed.
NLP researchers aim to gather knowledge on how human beings understand and use language so that appropriate tools and techniques can be developed to make computer systems understand and manipulate natural languages to perform the desired tasks. The foundations of NLP lie in a number of disciplines, viz. computer and information sciences, linguistics, mathematics, electrical and electronic engineering, artificial intelligence and robotics, psychology, etc. Applications of NLP include a number of fields of studies, such as machine translation, natural language text processing and summarization, user interfaces, multilingual and cross language information retrieval (CLIR), speech recognition, artificial intelligence and expert systems, and so on. One important area of application of NLP that is relatively new and has not been covered in the previous ARIST chapters on NLP has become quite prominent due to the proliferation of the world wide web and digital libraries. Several researchers have pointed out the need for appropriate research in facilitating multi- or cross-lingual information retrieval, including multilingual text processing and multilingual user interface
Data mining has four stages: collection, aggregation, interrogation and prediction (de Zwart et al 2014, p. 715-719). As with filtering, this process more often than not happens without the knowledge of users and regardless, it is “almost impossible” to prevent (p. 716). The importance of user consent has already been touched upon, as has the implications for the balance of power between social media platforms and the users. As social media implicitly exists for users to interact with one another , for the power to remain out of the hands of the users is especially problematic as it in many ways contradicts the supposed purpose of social media (Baym 2015, p. 1-2). More specific to data aggregation and interrogation, the power imbalance works against the freedom of expression and instead restricts the ability of the individual to control their own identity and the way it is presented. Data aggregation, or the collection of data over time, has no way or retaining context for specific actions or interactions (de Zwart et al 2014, p. 716). The previously discussed context collapse comes into play once more, as the way a individual may present themself in interactions with various other users may form what appears to be contradictory information. The interrogation of this data then becomes the
[2] Bonnie Dorr, Lecture note on CMSC 723: Natural Language Processing, University of Maryland, College Park, Spring 1996.