Venus Mohammadi; Mohsen Hosseinzadeh; Mehdi Hosseinzadeh Hosseinzadeh
Abstract
v Recommender systems utilization has proven sales enhancement in most e-commerce platforms. This system objected to provide more options, comfort and flexibility to user which could make him interested, as well as providing better chance for companies to increase sells in their products and services. ...
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v Recommender systems utilization has proven sales enhancement in most e-commerce platforms. This system objected to provide more options, comfort and flexibility to user which could make him interested, as well as providing better chance for companies to increase sells in their products and services. Flourishing popularity of web site has originated intrigue for recommendation systems. By penetrating in infinite fields, recommendation systems give deceptive suggestion on services compatible with user precedence. Integrating recommender systems by data management techniques to can targeted such issues and quality of suggestions will be improved considerably. Recent research reveals an idea of utilizing social network data to refine weakness points of traditional recommender system and improve prediction accuracy and efficiency. In this paper we represent views of recommender systems based on Twitter social network data by usage of variety interfaces, content analysis Methods, computational linguistics techniques and MALLET topic modeling algorithm. By deep exploration of objects, methodologies and available data sources, this paper will helps interested people to develop travel recommendation systems and facilitates future research by achieved direction.
Parvin Fakhri; Mahdi Hosseinzadeh Zadeh
Abstract
2016 USA presidential election results surprised many in America. Most experts and traditional polls had predicted that Hillary Clinton won election but results marked otherwise. In this study, with social network analysis method in content analysis approach, the election campaigns for the two main candidates ...
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2016 USA presidential election results surprised many in America. Most experts and traditional polls had predicted that Hillary Clinton won election but results marked otherwise. In this study, with social network analysis method in content analysis approach, the election campaigns for the two main candidates was investigated on the basis of tweets sent on Twitter platform during the three day period prior to November 8, 2016.It was found that in most analytical aspects such as analyzing tweets, retweets, hashtags, mentions words, user profiles and so on, Trump’s campaign advantage is evident and among users with a neutral trend Trump tendency is likely to dominate. In addition, we identify Some electoral strategies and effective political movements, for example, we understand that Clinton campaign focused on attacking Trump and vice versa Trump campaign focused on support Trump, or users, particularly neutral have shown particular attention to Wiki Leaks and disclosure of emails.
