Research Paper On Sentiment Analysis

Before the invention of Facebook, twitter, and many others, social media data collection was used by companies to get customers’ impression about their products. However, nowadays with modern technology the game has changed. Following the discoveries of these various social media networks, users are now capable of browsing vast bulk public postings, and others are taking advantage of it to commit crimes. This carnage of online crime has alerted the law enforcement to look ways to tackle it, hence starting to monitor and collect social media data. Collecting of social media data by law enforcement, is gathering of the users’ information, intercepts users’ communications, and analyzes that data to make intelligence determinations. This approach helps to disclose key information or secrets of online crimes to law enforcement. An online crime such as street gang and terrorism is not a new thing in the world today. Currently, terror and gang

With the growth of the internet, information dissemination has grown cheaper meaning that users can get access to information from any part of the planet from PCs and smartphones. This has in turn led to question marks in the information being disseminated through the internet given that there is no central figure to provide oversight or editorial work on content. This is especially the case with micro blogging websites like Twitter that are being leveraged as sources of information. Researchers have previously established that Twitter can be used in cases of emergency given that it can reduces the time in communication and in turns facilitates mitigation of such events. The challenge in this creative way of improving communication is in the difficulty in assessing credibility of information being posted a feat that is solved for by the ideas presented in this paper. The task tackled here is improving efficiency in real time Twitter credibility scoring systems

Emotionally tainted opinions are worthy of respect, and should be accepted as much as factual opinions but only after emotions aren’t running high. Not all factually set opinions are necessarily correct; some could be morally wrong. A few emotionally based opinions do have some facts behind them; it’s just that the other “opinion” is more accepted. A lot of people were brought up on emotional opinions and that’s what they strongly support, so they might overlook the facts. Emotionally biased opinions should be accepted as much as factual opinions.

The statistical analysis involvesexploring the correlation and regression among the research variables, as well as descriptive statistics such as means and standard deviation. Pearson correlations were calculated for the six variables measured by interval or ratio scales. It helps to measure the strength and directions of the linear relationship between two variables. In order to test the hypotheses, linear regression analysis can further examine whether there is an interdependent quantitative relationship between dependent and independent. Except for statistical analysis, descriptive analysis is also helpful for the illustration of consumers’ opinions. Graphs and figures are used to present consumer’s preference on publishing content from company social media account. Through the comparison between the actual content consumers have seen and ideal content they would like to see, it will be conductive to provide messages for companies to adjust their current posting contents to the content that are likely to cater to the tastes of online

Social media has become prominently popular. Tens of millions of users login to social media sites like Twitter to disseminate breaking news and share their opinions and thoughts. For businesses, social media is potentially useful for monitoring the public perception and the social reputation of companies and products. Despite great potential, how bad news about a company influences the public sentiments in social media has not been studied in depth. The aim of this study is to assess people’s sentiments in Twitter upon the spread of two types of information: corporate bad news and a CEO’s apology. We attempted to understand how sentiments on corporate bad news propagate in Twitter and whether any social network feature facilitates its

Web analytics is a very powerful tool that involves collecting, analyzing, measuring and reporting the traffic on the website with their behavior which optimizes the success of the site. Analytics data are used to focus on the wealth of information about business and customers. Analytics helps measuring & analyzing the customer’s interest on a product which can help attract

Reviews offer a limited number of opinions, and they generally focus on one particular topic. There is also some bias in the reviews. People who have very strong feelings about something in a company tend to share their opinion in a form of review. Mostly, those reviews display customers’ overwhelming dissatisfaction with something or customers’ excitement about purchased products. Customers’ feeling should be strong enough to give them enough incentive to take their time and write a review. However, this is not the only way to identify customers’ awareness and opinion on companies’ reputation, price, quality, brands, product range, and customer. The social networks can provide us with a variety of opinions that fall in various categories of a conversation. We can compare

Web analytics is characterized as a sway 's examination of a site on its clients. E-trade organizations and other site distributers regularly utilize web investigation programming is to quantify such solid subtle elements as what number of individuals went by their website, what number of those guests were novel guests, how they went to the webpage, what decisive words they sought with on the webpage 's internet

Web analytics is the practice of measuring, collecting, analyzing and reporting on Internet data for the purposes of understanding how a web site is used by its audience and how to optimize its usage. There are five steps in this continuous and repetitive process: Collect, Measure, Report, Analyze, and Optimize. First of all, the analyst needs to identify the client’s goals and objectives. This is to make sure that both of them are on the same page and looking to achieve the same target. Any discrepancy or misunderstanding in this step can cost a huge amount of time and efforts later when they move along with the project. The goal categories are Revenue, Acquisition, Inquiry, and Engagement - the larger business objectives that most campaigns seek to accomplish. Some typical objectives can be, for example, leverage brand image or boosting sales. Second, the analyst uses web analytics software to collect relevant data. This web analytics software can be Google analytics, a free tool that is provided by Google. Next, the data is to be compiled in

There are many objectives of data mining like transform raw data into beneficial knowledge, calculation (analytical data mining is common type of data mining and has most direct business application). This makes it difficult for a potential customer to read them in order to make a decision on whether to buy the product. Usually seller who wants to sell products on the Web ask their customers to comment and opinion for the products and services. As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. For a popular product, the number of reviews can be in hundreds. This summarization task is unlike traditional text summarization because it is only involved in the exact features of the product that customers have opinions on and also whether the opinions are positive or negative. Do not summarize the reviews by selecting or rewriting a subset of the original sentences from the reviews to capture their main points as in the classic text summarization. A number of procedures are presented to mine such features. Stage for customer’s review mining:

Yang Peng, Melody Moh, Teng-Sheng Moh, Efficient Ad- verse Drug Event Extraction using Twitter Sentiment Analysis , in this they proposed a simple, efficient pipeline for retrieving ADEs. Any selected drug should have been in the market for more than ten years. Following this rule, there are sufficient number of tweets exist for any selected drug. Drug related classification is done on preprocessed Data. Sentimental Anal- ysis. 5 times

In this paper we different techniques which is used for domain analysis, feature recommendation. This approach mines descriptions of product from publicly available online product Descriptions, used a text mining and a novel incremental diffusive clustering algorithm to discover features in specific domain , use association rule mining to know latent relationships between features within products of same domain and used KNN algorithm for generates a probabilistic feature model that represents commonalities, variant.

The approach used in this thesis is inspired by Bollen et al’s strategy [12], with a step taken forward to implement PageRank algorithm to increase the accuracy of results and use of different sentiment analysis techniques than the techniques used by him. In 2010, Bollen used Twitter data for finding the predictability of Twitter sentiments on stock market with high accuracy. He proposed a method for prediction of the changes in the stock market price based on the mood of people on Twitter.

this research analysis that automatic detection of online terrorist recruitment is a feasible goal and

Existing work has been done about the role of Twitter as tracking tool to validate real-time content, sentiment and public attention trends.