Research Frameworks Used For Mining And Summarization Are Been Search By People For Gathering The More And More Information Essay

In this paper we will be looking at search engines, social media and blogging and try and way up

Social media is a term we use daily in our lives and is a trend that continues to grow at a very rapid pace like technology. Not only do we as individuals use social media to post life events and share photos to friends and family, but we also have the habit of using it for first impressions of others and broadcasting small town news. Whether we realize it or not, newspapers and face to face conversations are becoming a thing of the past in our generation. Just like everything else created, with the good also comes the bad. Social media is a blessing and a curse in the healthcare industry.

The use of social media can be very beneficial to health care in different ways, including fostering professional connections, promoting timely communication with patients and family members, and educating and informing consumers and health care professionals. Social media is changing the way that health professionals and patients interact with each other. The use of social media and other electronic communication is expanding exponentially as the number of social media outlets, platforms and applications available continue to increase. Individuals use blogs, social networking sites, video sites, online chat rooms and forums to communicate both personally and professionally with others (NCSBN, 2011).

What is communication? Communication is the process of sharing information, thoughts and feelings between people through speaking, writing or body language. Communication then becomes effective when the information given is understood by the person who it was given to. Communication is vital when it comes to healthcare by effectively providing information to the patients and their families and also conversing with employees in directing proper health care facilities. Communication may be the key to exceptional patient care. The case can be made that good communication is at the heart of patient safety, cultural sensitivity, and the pillar of healthcare. Aligning a patient’s wishes and goals with treatment plans

Health policies in various regions have begun to acknowledge and recognize health information as an instrument for engaging patients, of cultivating devotion to treatments and of enabling informed choice. The impressive transformations in emerging technology have essentially altered the way the public gains access to information. In the future, they will most likely portray meaningful impact on the way the public and patients communicate concerning health and how they provide their feedback over their needs and opinions into more patient-centered health facilities (Cui, Carter & Zhang, 2014). Producers of information are also shifting, to audience-particular, multi-format, and user-led resources. They are sincerely starting to refine the experience of patients. The motive of health information benefactor is widening to integrate a wide variety of non-health fields including libraries, domestic councils, and schools. However, these transformations are also introducing new problems. For instance, large segments of the United Kingdom population lack admittance to relevant information that caters to their health needs. According to Abaidoo (2014), the value of health information differs enormously and not all people are able to enjoy the opportunities, which are offered by the new technology. Consumer health information

How information is collected, distributed, searched and consumed on the Internet has created huge ripple effects that it impacts not just businesses and journalism, but crosses into politics, medicine, and media. Ultimately, it affects the average person’s day-to-day lives.

With the development of the Web 2.0 which made Internet participative, the Internet users are now capable of expressing themselves, interacting, and giving their opinion onto everything (products, services, brands, companies, cultural property) and on everybody, via multiple platforms on Internet. To criticize a restaurant on Cityvox, to note a seller on eBay, to denounce the actions of a brand or a company via a viral video on YouTube, to support a candidate for an election, to

In today’s world Internet has become one of the most important mediums of communication. It has become the lifeline of our survival. It has removed the entire social, economic and physical barrier and has immense effect on our day to day activity.

Social media has made an impression in every dimension of our lives, the dimension of healthcare is not far away, and is indeed catching up pretty expeditiously. In recent times, with emergence of social media era, "the freely available web-based platforms that facilitate information sharing of user-generated content, such as social networking sites, media-sharing sites, blogs, micro blogs, and wikis, has benefited the healthcare areas in many ways by playing the crucial role" (American Heart Association, 2013). However, the open and communizing shape of social media generates a number of potential risks, both at individual and organizational level.

Nowadays, social media and Internet became part of daily life. People spend more and more time going online. Many daily activities shifted to online, for example, online shopping, communicate with friends or relatives via social media or messaging app, share feelings and thoughts on social media platforms etc.

Opinions play a crucial role in the decision making process. Analysis in the field of making decisions and setting policies has shown that sentiment analysis and Opinion mining has become increasingly important in the field of Information Retrieval and Web analysis. In the past years, the growth of user generated data in web forums, social networking sites and other social platforms is tremendous, which diverts our study towards mining the opinions on web. In this paper, we have presented a novel methodology to classify the tweets and the complete opinion mining system is explained on the basis of survey and analysis. A flowchart has been proposed in which the overall picture of classification of twitter data has been proposed and accuracy of the evaluation strategies by various supervised learning algorithms has been evaluated. Review data is collected for various product domains from micro blogging sites like twitter, face book.

Very soon in the explosion of internet, various companies helped provide the demassification of internet. But this demassiffication would be like no other before. A regular demassification process affects genre, selects viewers, and slices its general content to a more specified one, to match the taste of their customers. The internet was totally different, by giving the publishing tools directly in the hands of users, and an easy but revolutionary statement could be made: “One user on the internet = one content”

Social opinion has been analysed using sentiment analysis (SA). This is basically a natural language processing (NLP) application that uses computational linguistics and text mining to identify text sentiments as positive, negative and neutral. This technique is known as emotional polarity analysis which is related to text mining field, opinion mining and review mining. In addition, to calculate sentiment score, the sentiment acquired from the text is compared to a dictionary in order to determine the strength of that sentiment. Studies on sentiment analysis focus on text written in English such as sentiment lexicons while applying this to other languages will cause domain adaptation problem [12]. Traditional text classification is different from sentiment classification. Traditional text classification refers to pre-defined class to determine a document’s category, and it gauges the theme of the text itself, while the main aim of the latter is to determine the attitudes and opinion through mining and analysing user interest or other subjective information [13]. Studies in sentiment analysis have found that pre-processing the data is the procedure of cleaning and adapting.

If we go back to history, two decades ago, people used primitive message boards or emails to talk to one another and a business would communicate via text-ads or pop-ups on search engine/directory like Yahoo. (Bolman, 2015, Para 4) Then in 1997, two Stanford Ph.D. students invented an algorithm named PageRank. The PageRank calculated the importance of the website based on how often other sites would link to it. Later, with the introduction of ‘Google,’ the first wave of technology began. This invention put the modern day internet in motion. (Bolman, 2015, Para 5) This essay paper is about the modern day internet and the technological uses in our daily lives. This paper will take a closer look at how we communicate on the internet and discusses about the major network building blocks and their functions, including some vulnerabilities associated with the internet software applications.

This article investigated some of the fundamental research issues inside of the field of sentiment analysis and examined several algorithms that intend to understand each of these issues. It has also portrayed a percentage of the major applications of sentiment analysis and gave a couple significant open difficulties. Numerous commercial sentiment analysis systems still utilize oversimplified systems so as to maintain a strategic distance from these open difficulties also, subsequently their execution takes off a ton to be sought. Giving satisfactory answers for these difficulties will make the region of sentiment analysis significantly more widespread across the board. Sentiment analysis (or Opinion mining) is characterized as the errand of finding the opinions of creators about particular elements. The choice making procedure of individuals is influenced by the conclusions shaped by thought leaders and ordinary individuals. At the point when someone needs to purchase an item online he or she will commonly begin by hunting down surveys and opinions composed by other individuals on the different offerings. Sentiment analysis is one of the most sizzling research regions in computer science. With NLP, while handling the configuration of cognitive systems, a noteworthy zone of work goes for empowering machines to prepare both composed and spoken types of common