Social Media Aided Sentiment Analysis in Forecasting K.Nirmala Devi, Kongu Engineering College, India Abstract User generated contents on web and social media grow rapidly in this emerging information
نویسنده
چکیده
User generated contents on web and social media grow rapidly in this emerging information age. Social media provides a platform for people to create contents, share them and bookmark them in a tremendous way. The exponential growth of social media arouses much attention on the use of public opinion to make better decisions about a particular product or person or service. The social media like online forums, Twitter, Facebook, blogs and microblogs are proving to be extremely valuable resources for anticipating, detecting and forecasting significant societal events. It provides a lot of opportunities for users to voice their opinions openly. The analysis of sentiments obtained through social media along with wisdom of crowds can automatically compute the collective intelligence of future performance in many areas like stock trend forecasting, box office sales, hot topic detection, election outcomes and so on. The proposed research aims to perform forecasting based on user sentiments in social media regarding hotspots and stock forecasting.
منابع مشابه
Content Strategy and Fan Engagement in Social Media The Case of PyeongChang Winter Olympic And Paralympic Games
Background. This paper investigates the pillars of content strategy and fan engagement in social networks during 2018 PyeongChang Winter Olympics and Paralympics. Objectives. The purpose of this paper is to seek reasons behind the differences in fan engagement in social media channels of PyeongChang Winter Olympics and Paralympics. Methods. Facebook and YouTube channels are used to analyze en...
متن کاملSimilarity measurement for describe user images in social media
Online social networks like Instagram are places for communication. Also, these media produce rich metadata which are useful for further analysis in many fields including health and cognitive science. Many researchers are using these metadata like hashtags, images, etc. to detect patterns of user activities. However, there are several serious ambiguities like how much reliable are these informa...
متن کاملOn Social Network Web Sites: Definition, Features, Architectures and Analysis Tools
Development and usage of online social networking web sites are growing rapidly. Millions members of these web sites publicly articulate mutual "friendship" relations and share user-created contents, such as photos, videos, files, and blogs. The advances in web designing technology and fast growing usage of online resources prompted web designers to improve features and architectures of social ...
متن کاملOn Social Network Web Sites: Definition, Features, Architectures and Analysis Tools
Development and usage of online social networking web sites are growing rapidly. Millions members of these web sites publicly articulate mutual "friendship" relations and share user-created contents, such as photos, videos, files, and blogs. The advances in web designing technology and fast growing usage of online resources prompted web designers to improve features and architectures of social ...
متن کاملUsing Machine Learning Algorithms for Automatic Cyber Bullying Detection in Arabic Social Media
Social media allows people interact to express their thoughts or feelings about different subjects. However, some of users may write offensive twits to other via social media which known as cyber bullying. Successful prevention depends on automatically detecting malicious messages. Automatic detection of bullying in the text of social media by analyzing the text "twits" via one of the machine l...
متن کامل