Clustering and Opinion Mining
Answer:
Introduction
Owing to social media’s massive popularity, currently business organizations are using social media tool as a medium to promote business and commerce in the form of advertisements and promotional videos. As a result, the companies have been able to reach to more people all over the world (Chen & Zhao, 2012). Moreover, due to the interactions in the social media, many companies have also joined together for collaborative ventures in the field of commerce. This report mainly emphasizes on the development of social media and the business collaborations that have grown from the social media.
Social Media and Business Collaboration Projects
Social medium is referred to the websites that are specifically designed to create friendships between people all over the world. With the progress of digitalization and virtualization in the modern era, people sought after some kind of medium that would enable them to stay connected to each other even though they are far apart (Aral, Dellarocas & Godes, 2013). In order to make up for this need, developers started designing some websites that would enable people to connect to each other in form of text messages, photos, videos and others. Thus, developers started developing some websites and Orkut, Facebook, Twitter and other popular websites came into existence. Every year, the number of subscribers of these websites started rising and currently, almost one-third of the world’s population are connected to social media. This also resulted in development of online business promotions and collaboration projects grew up between many companies.
The arrival of Web 2.0 in the first decade of the 21st century quickened the development of social networking sites. Web 2.0 destinations ar
e those that permit ease of use of client produced content. This permitted cooperation and coordinated effort amongst people and associations over the web utilizing exchanges of words as a part of a virtual domain. Communication may be in type of trade of assessments in discoursed, production of hypothesis and its input in a blog, and so forth (Anjaria & Guddetti, 2013).
Cambria et al. (2013) researched on the development of social media and its effects on business promotions and collaborations projects and they prepared some basic models. One of the models was based on etymological investigation and was proposed by Liu (2012) and the other accentuated on the examination of technical learning strategies.
Attributable to enormous ubiquity of a medium, specifically the social media, it has rapidly turned into a subject of research for the cooperation examiners and sentiment miners (Khan, Atique & Thakare, 2015). Social networking is a miniaturized scale blogging website, where a feeling from a specific individual must be communicated in a basic dialect and in a little size. The miniaturized scale blogging stage goes about as a noteworthy wellspring of individuals' sentiment. This is on account of, these days, general mass, lawmakers, sportsmen, big names alike utilize social media and all express their assessments or perspectives over a specific subject through social media. Huge quantities of posts are made in social media consistently, and henceforth, accumulation of a specific information turns into a troublesome errand. In this way, use of mechanized information accumulation framework gets to be vital (Maynard, Bontcheva & Rout, 2012).
Genuine uses of association examination have been the primary reason of development for different enterprises. Organizations got orders for a specific item, client criticisms and conclusions for further advancement of the organization through the web-based social networking. Development and thriving of organizations like Microsoft, HP, Google and a few others gave inspiration to further research of collaboration examination on the social networking (Liu, 2012).
Other than these genuine applications, a few research papers were distributed amid different periods, which were situated on application-based investigation. Connection investigations can be utilized for forecast of offers result, rank traders and items, or even expectation of consequences of an open decision (Maynard, Bontcheva & Rout, 2012). Social networking examination gives the pattern of political angle inside general mass.
Currently, business organizations are using social medium as a place to promote business and commerce in the form of advertisements and promotional videos. Due to the interactions in the social media, many companies have also joined together for collaborative ventures in the field of commerce. For example, according to a popular case study (Aral, Dellarocas & Godes, 2013),
“Toronto-based Goldcorp, a gold mining firm, looked for another way to deal with discovering gold stores on their 55,000-section of land Red Lake, Ontario property. With examiners trusting that the fifty-year old property had been purged, high creation costs, work strikes and waiting obligation, the firm was frantic to discover new life. Without choices, CEO Rob McEwan made the Goldcorp Challenge whereby he put each bit of data about the property on the web for all members to download, concentrate on and submit suggestions. More than 1000 members from more than 50 nations joined to take care of Goldcorp's issue. Entries originated from a different gathering of members, numerous not prepared in geography. This open-source advancement sequence ended up being significant recognizing 110 targets worth more than $3 billion.”
Another well-known example can be stated as follows (Aral, Dellarocas & Godes, 2013).
“In mid-2007 IBM made Beehive, an inner informal organization to associate representatives around the world. The system picked up force and backings 30,000 representatives. Every worker can include a bio page, photographs and interface with representatives from other IBM workplaces around the globe. What is fascinating about Beehive is the way the representatives utilize the inner system. There are three particular classifications of utilization. The first is to interface with representatives they meet at meetings or when chipping away at interdepartmental or between divisional tasks. The system gives a component to remain associated and become more acquainted with different workers and their range of skill. The second utilize is to pick up venture support and conceptualize with others on how best to finish a venture. The associations give a cooperation channel to elevate the venture to others and accumulate thoughts from other individuals at various levels.”
Another common example of collaboration project through social media is collaboration between Facebook and Workplace. Facebook is a social networking site where users can contact with each other over the virtual interface whereas Workplace is a social medium site that mainly deals with job openings for all the users. At some point in the second decade of 21st century, Facebook noticed the prospect of Workplace and started collaboration with the company in the name of “Workplace by Facebook”. The move was immediately popular and the number of Workplace subscribers rose significantly.
These examples depict some collaboration projects as conducted by some popular companies. Following these examples, more social media sites were developed (e.g. LinkedIn) that created direct connections between business organizations so that the promotional activities do not get hidden among normal social connection activities (López, Tejada & Thelwall, 2012). As a result, more companies came together and started collaborating with each for conducting large scale projects. In 2016, two popular social media websites Facebook and WhatsApp collaborated with each other and started functioning together as one company. Even more social media sites also came together for collaboration that ultimately resulted in development of business and popularity of the sites.
In spite of all the popularity of social media in the field of business and commerce, it itself presents several challenges to the business interactions analysis research. First, deviation of discussion from the main topic and use of irrelevant comments, often non-suitable for young viewers, poses a major threat to the study. Because of this particular problem, some contents cannot be shown to some viewers, and a definite general opinion cannot be evaluated (Petz et al., 2013). To get rid of this problem, several classifier personnel should be trained to classify comments and remove irrelevant ones. Clustering opinions regarding same topic can also be done to remove unwanted comments. Secondly, using the search function of the website may not always bring desired results. This happens when several discussions have been conducted on very similar topics and when searching for one particular discussion using search operator, all the discussions are presented (Nakov et al., 2013). This problem can be solved by using an approach that is entity specific. That is, a search can be made on a specific entity and then finding relevant discussions on that entity. Thirdly, another important threat is negation. According to Liu (2012), researchers cannot handle negative opinion properly when there is no proper definition of the amount of negativity. Subtle differences between two different usages of the same word can be hard to analyze in a suitable manner. Fourthly, use of some high-level world knowledge, which might not be accessible to all users, poses a threat of confusion within a media discussion. For example, one may compare to one real world entity to a fictional character, which in spite of being popular, might not be a part of knowledge of some other discussion member (Selvan & Moh, 2015). On the contrary, this can be useful to some extent, as it may increase stock of knowledge of an individual and sometimes, provides important information not known to some.
Finally, there are few points to be noted. Use of social media as a medium for business collaboration or collaboration projects is a very good idea as it gives the small and medium sized organizations more global exposure (Kim & Kim, 2014). With this global exposure, the companies can grow easily. Again, collaboration projects also benefits both the companies and hence, one company can have the share of profit from the other company’s prospects. This is how, a small company can grow and one day become a large multinational business organization (Cooper, 2013). However, there are some issues as well. These issues include security issues and fraud cases that severely damage a business organization. There are many fake companies available in the social media that take advantage of the collaborating company’s trust and steal confidential files, money or even identity of the company (Zhou et al., 2015). Hence, verification and cross-checking is necessary before starting collaboration with another company through social media.
Conclusion
From the report, a number of things can be concluded regarding the existence of large collaboration projects that have been possible only because of the existence of the social media. Before concluding about the collaboration projects, it is clear that social medium is currently an inseparable part of business of the large business organizations. Owing to the massive popularity of social media, currently large business and ecommerce organizations are using social medium as a place to promote business and commerce in the form of advertisements and promotional videos. As a result, the companies have been able to reach to more people all over the world. Moreover, due to the interactions in the social media, many companies have also joined together for collaborative ventures in the field of commerce. As a result of promotions through social media websites, many well know business organizations like IBM, Goldcorp collaborated with other organizations to complete some large scale projects in their business fields.
Recommendations
As a result of the study, some recommendations can be prepared for further increasing the collaborative projects in the future. These are as follows.
Collaboration and Promotion – More business organizations (small and medium sized) should use social media as a medium for promoting business. These will allow other companies to know more about them and some of the companies may choose to collaborate with them for executing some projects.
Legitimacy – Before starting collaboration with any another company, one organization must check its legitimacy and business history as there are already numerous fraud companies present in the social media.
Security – Use of social media should be limited to certain extent in order to maintain security of the organization’s server system. As there are many security threats lurking in the social media, it is best to use them with strong security measures.
Internal Details – The business organizations that are looking for collaborative projects in the social media should only share the essential details of the organization. The business strategies should never be disclosed in the social media.
References
Anjaria, M. & Guddeti, R.M.R. (2014), January. Influence factor based opinion mining of Twitter data using supervised learning. In Communication Systems and Networks (COMSNETS), 2014 Sixth International Conference on (pp. 1-8). IEEE.
Aral, S., Dellarocas, C., & Godes, D. (2013). Introduction to the special issue-social media and business transformation: A framework for research. Information Systems Research, 24(1), 3-13.
Cambria, E., Schuller, B., Xia, Y. & Havasi, C. (2013). New avenues in opinion mining and sentiment analysis. IEEE Intelligent Systems, (2), pp.15-21.
Chen, K. & Zhao, H. (2012). Twititude: Message Clustering and Opinion Mining on Twitter. 2012.
Cooper, G. (2013). Opinion Mining with Twitter Course: MT8902–Major Research Project.
Khan, A.Z., Atique, M. & Thakare, V.M. (2015). Combining lexicon-based and learning-based methods for Twitter sentiment analysis. International Journal of Electronics, Communication and Soft Computing Science & Engineering (IJECSCSE), p.89.
Kim, D. & Kim, J.W. (2014). Public Opinion Mining on Social Media: A Case Study of Twitter Opinion on Nuclear Power. Proceeding of CES-CUBE,2014.
Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis lectures on human language technologies, 5(1), pp.1-167.
López, R., Tejada, J. & Thelwall, M. (2012). Spanish sentistrength as a tool for opinion mining peruvian facebook and twitter. Artificial Intelligence Driven Solutions to Business and Engineering Problems, pp.82-85.
Maynard, D., Bontcheva, K. & Rout, D. (2012). Challenges in developing opinion mining tools for social media. Proceedings of [email protected] NLP can u tag# usergeneratedcontent, pp.15-22.
Nakov, P., Kozareva, Z., Ritter, A., Rosenthal, S., Stoyanov, V. & Wilson, T. (2013). Semeval-2013 task 2: Sentiment analysis in twitter.
Petz, G., Karpowicz, M., Fürschuß, H., Auinger, A., St?íteský, V. & Holzinger, A. (2013). Opinion mining on the web 2.0–characteristics of user generated content and their impacts. In Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data (pp. 35-46). Springer Berlin Heidelberg.
Phan, D.H. & Cao, T.D. (2014), December. Applying skip-gram word estimation and SVM-based classification for opinion mining Vietnamese food places text reviews. In Proceedings of the Fifth Symposium on Information and Communication Technology (pp. 232-239). ACM.
Selvan, L.G.S. & Moh, T.S. (2015), June. A framework for fast-feedback opinion mining on Twitter data streams. In Collaboration Technologies and Systems (CTS), 2015 International Conference on (pp. 314-318). IEEE.
Sidorov, G., Miranda-Jiménez, S., Viveros-Jiménez, F., Gelbukh, A., Castro-Sánchez, N., Velásquez, F., Díaz-Rangel, I., Suárez-Guerra, S., Treviño, A. & Gordon, J. (2012). Empirical study of machine learning based approach for opinion mining in tweets. In Advances in Artificial Intelligence (pp. 1-14). Springer Berlin Heidelberg.
Zhou, X., Coiera, E., Tsafnat, G., Arachi, D., Ong, M.S. & Dunn, A.G. (2015). Using social connection information to improve opinion mining: Identifying negative sentiment about HPV vaccines on Twitter. Studies in health technology and informatics, 216, p.761.
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