Big Data Assignment: Research on Hotspot & Online Public Opinion
Task: This big data assignment expects the student to submit a critique report on a research article related to a Big Data and its current trend technologies. This assessment is designed to improve student presentation skills and to give students experience in researching a topic and writing a report/Critique report relevant to the Unit of Study subject matter. The research articles would be tasked to explore further research trends relevant to the unit content. As further research findings evolve the unit lecturer may supplement or substitute these to keep the research delivery current and updated.
For this component you will prepare a report/critique on an academic paper related to Big data or big data technologies, Big data analytics, Big data security etc. The paper you select must be directly relevant to one of these major topics. The paper can be from any academic conference or other relevant Journal or online sources such as Google Scholar, Academic department repositories etc. The topic and the related paper need not be later than 2013-14.
The report on big data assignment brings forward essential traits supporting big data development and the online public opinion in the Big Data environment. Massive volume of data influx which can be both unstructured and structured can be described as Big Data. On a regular basis, organizations generate these huge chunks of data, now the significance of the data lies in the fact how the organizationsutilize these data. The utilization of the data in the right manner will ensure to have grip on the matter of research and it will right analytical tools, the results will be accurate. In recent times, the presence of online public opinion is seen to create certain challenges for the old traditional means of data analysis. Velocity of data is referred to the speed at which data is being generated and processed for meeting demands. This character determines the true potential of data. Big data holds the features of rapid growth, multi modality and scalability that pose serious challenge for tradition means of analysing the content of data in regard to public opinion in a big data environment.
Review and analysis
Big Data has been influencing the global society in a great manner in all fields of work. To understand the various existing trends, future trends and hotspots in the field of research of public opinion in big data ambience, the authors used secondary method of research, involving collection of various journals and published on the same aspect and deriving additional results from it. The authors then performed visualization analysis and bibliometrics analysis to understand the trends and hotspots to provide insights on the subject of research. The significance of big data revolves on the utilization of the data as it brings about outside intelligence in the decision making process and improves services drastically. Big Data provides methods aids in cost advantages by analyzing efficient ways of performing operations. As mentioned by the authors, big data reduces analyzing and consumption time as new techniques of analysis provides both quicker and accurate results. Big Data tools are also designed to perform sentiment analysis. Sentiment analysis provides a way for companies to monitor feedback for improving online performance.
Data that can be accessed and also processed in a pattern of a fixed structure is called as a structured data. High valuation and knowledge is derived from such sets of data . In case of an unstructured data, the data set available is of the unknown form or it in a classified form. Given the volume of data, unstructured data poses major challenges when it comes to processing of data and derivation of value and a semi structured data contains data of both kinds. Rightly mentioned in the article, recent times with the advanced development and application of this new technology has brought about far reaching alterations in multiple fields of business and operations in regard to the growing global economy . Institute and companies is seen to utilised big data for their growth and development, and with the rise of online public platforms, there is a sudden surge in the quantity of online public opinion data and the diversity of the same data - an observation made by the authors.
The rapid advancement of online public opinion has now turned into a research for enterprises and government bodies as mentioned by Wang . In this era of Big Data, network analysts working on public opinion keeps their focus primarily on mining crucial information from the data set by utilising certain big data technologies available in the market. As Wang mentioned, this provides exclusive information to provide decision support and at the same time there are multiple challenges when compared to the traditional model of analysis of online public opinion data . The collection of data and different public sources holds valuable information in understanding the research done so far in the respected field as seen in the research paper of "Research on Hotspot and Trend of Online Public Opinion Research in Big Data Environment". Published articles of the top ten cited documents are utilised which includes the intelligence magazine, young journalists, news research guides, modern intelligence, information theory and practice, Information science, China Management, E-government, Industry and technology forum. These papers had topic inclusion of public decision and opinion in relation to big data ambience and it is observed that there is an exploration of methods, theories and features involving chief technology in regard to mining and decision analysis of public opinion.
Implication and interpretation of online public opinion in a Big Data ambience
Literature provided by the authors gives insights into multiple methodologies and similarly challenges involved in the same. Visual and quantitative analysis of data enabled in the creation of developing and exploring new arenas in relation to mining based technologies to extract maximum information. Given the unqualified richness of the data sets which are received and the diversity of the information of the same provides a thorough insight about the perception of the newest trends and hotspot in the Big Data environment . There has been a steep rise in the annual document age distribution in regard to research done on several big data environment as mentioned by Wang . The article on "Research on Hotspot and Trend of Online Public Opinion Research in Big Data Environment" holds valuable information about the distribution of research over the years and notable delays in certain years. At the time when Big Data technology has emerged, it set ground for several research works which lead to the advancement and extreme development in this field . At a time when there is a growth in sustainable methods of life and working in business, Big Data will be of essential help in creating difference in the business sectors as believed by the authors basing on facts. Analysing the sources, shows that there are many journals that provide strong support in conducting research in the online public opinion field in a big data ambience. The article emphasizes on the importance of information science and library in the field of public opinion of the big data network. Further research on understanding the trends shows that the force of research seems to be concentrated in universities and colleges, the focus lies mostly on management, computer science and journalism. There has been an institute in Beijing China that has opened up an public opinion research centre which is co organized with sympathetic internal resources. Research shows multiple colleges and universities are funding several researches and increasing their efforts in supporting research for this interesting topic . Going by the kind of domestic research groups it can be said that these are scattered in the field of research of public opinion in a big data environment.
There is less amount of cooperation amongst the companies and the relationship sustained is not strong.
There is a platform for utilizing the certain advanced analytics techniques like that of machine learning, text analytics, natural language processing and predictive analysis for getting further insight regarding public opinion in big data environment. Information from previous untapped sources of data bounded together or independently exists with the data of several enterprises. There are multiple use cases when it comes to big data application. Aggregation of several data provides crucial touch points for companies and even institutes to understand their and gain a holistic vision of the motivational aspects and at the same time improve tailor made services and products. Here the data sources from where the public opinion is acquired are that of mobile devices, sentiment and various social media platforms . It enables in the mitigation of fraud cases as monitoring of transactions can be done in real time. The real time analysis provides proactive recognition of abnormal behavioral patterns in usage and transactions indicating a mighty occurrence of fraudulent activity. Such activities are easily mitigated and nullified through prescriptive and predictive analytics of old data . It essential to ensure integrity of the data lake through proven governance solutions which provides the drive for better integration of data security, quality and integration.
In the context of understanding public opinion in a big data environment, the evolution of such a field can be analyzed with the given number of words that have appeared revealing the trends and hotspots of the research. In the field of public opinion research there are major ten hotspots with high frequency in the big data environment. The keywords are mainly are big data with a frequency of 216, internet sensation with a frequency of 168, public opinion analysis having a frequency of 54. Hadoop holding a frequency 31, data mining having a frequency 26, social sentiment having a frequency 19, then public opinion monitoring having a frequency if 17, lyric information with a frequency of 12 and lastly emotional analysis holding a frequency of 11. When comparison was conducted with the traditional set of data oriented public opinion in the big data environment, the focus lies mostly on the storage, cleaning and collection of large chunks of data. In a similar fashion text mining or data mining is applied for obtaining public opinion research information. Given the keyword analysis with their respective frequencies combined with the hot topic and data network of the public opinion, the research in the big data environmental field can be segregated into four parts or aspects. On analysis of each aspect, valuable information is extracted regarding hotspots and trends The first aspect is having a sharp focus on the hot research fields of the public opinion theory and the various methods available in the bid data environment. There has been further discussion related to the network of public opinion in big data in the light of new found problems, methodology and the direction of future research in the field. While working on this particular aspect it is significantly crucial to provide innovative means of analysis which emphasis on the accessibility, security and representativeness.
The proposed outlet for further research by the authors included expansion of data source, processing structure of big data, result visualization of big data and storage intensification of big data. The second aspect is focusing on data acquisition like that of Hadoop, cloud computing, public opinion information and network crawler . Network public opinion data collection in big data ambience involves storage as well as crawling of big data public opinion information. With the onset of Big Data, the new technology challenges the traditional model of data collecting techniques. There have been efforts made to improvise framework while utilizing distributed web crawlers for the completion of rapid big data collection in relation to network public opinion with extremely high scalability and efficiency. The third focus aspect is on the data processing background like that of emotional analysis and public opinion monitoring. There has been significant improvement made in the parallel processing technology which is used in the extraction of feature vectors and at the same time calculating matrix vector multiplication of the public opinion texts. Bayesian three-layer clustering algorithm for the purpose of mining multi-domain real-time data of hot topics which are used with the combination of HBase for the completion of processing and storage of bulk data on public opinion information. The fourth focus aspect is on the process and point of assessing public opinion level which are in accordance to the results of the processing of big data and other guiding measures. Statistical analysis and log mining are utilized for studying government network public opinion data and then comprehending user behavior for serving optimizing strategies and decision making . In a way mining of big data in relation to network public opinion aids in identifying, predicting, determining and evaluating plans and goals . On the other hand, provides a platform which can aid in improving evaluation and decision feedback.
The authors provides certain evidences which enables to conclude that in the time to come there will high advancements regarding future prediction of online public opinion on a Big Data environment. The research trend analysis shows there was an initial research phase at the beginning of the decade where proceedings were slow as then the concept of big data was new to the public. Here work was performed to understand challenges and problems on online public opinion. The rapid development phase started near about two three years later from the initial phase and the ground were strong and there was heavy influx of information. Work was done on new frameworks and other technology segmentation for completing the analysis of public network opinion in a big data ambience. Few years from there, the multi development phase started which lead to raid and sustainable growth of this field paving roads for further research. These researches have been applied to information of food safety opinions and other fields of daily business operations through various cloud platforms. The information gathered will prove to be provide immense aid to government bodies to understand public opinion and thus aid in the decision making process and improving strategies in public opinion mechanism.
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