http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : ( Tassawar Iqbal ) (검색결과 2 건)
- 무료
- 기관 내 무료
- 유료
-
There's No Such Thing as Free Lunch but Envy among Young Facebookers
( Tassawar Iqbal ),( Muhammad Tariq Yousafzai ),( Sabeen Ali ),( Kinza Sattar ),( Muhammad Qaiser Saleem ),( Usman Habib ),( Atta Ur Rehman Khan ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.10
Facebook has quickly infused across cultures worldwide to become a common household term for diverse spectra of netizens, especially youngsters. Inherently, interactive in nature, Facebook provides a common cyber enabled platform for online interactions with social friends, living across the world. However, despite its merits, users also experience certain disadvantages, which include but are not limited to rise in feelings of social comparison, decline in self-esteem, contentment and general subjective well-being. This work aims to determine the role of Facebook in spreading envy and identify factors that trigger such emotions. Due to abductive nature of the study, we used pilot interviews and consulted relevant literature to formulate hypotheses. Further, we used deductive approach and conducted a survey. The results showed that frequent use of Facebook, particularly passive following is main predictor of envy, and social interaction is the biggest cause for development of envious feelings in Facebook users. However, insignificant variation was found while investigating relationship between envy and factors, such as pretentiousness, time spent, accomplishment, everything in life, likes on posts, popularity across genders, marital status and genre.
-
Finding Rotten Eggs: A Review Spam Detection Model using Diverse Feature Sets
( Abubakker Usman Akram ),( Hikmat Ullah Khan ),( Saqib Iqbal ),( Tassawar Iqbal ),( Ehsan Ullah Munir ),( Dr. Muhammad Shafi ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.10
Social media enables customers to share their views, opinions and experiences as product reviews. These product reviews facilitate customers in buying quality products. Due to the significance of online reviews, fake reviews, commonly known as spam reviews are generated to mislead the potential customers in decision-making. To cater this issue, review spam detection has become an active research area. Existing studies carried out for review spam detection have exploited feature engineering approach; however limited number of features are considered. This paper proposes a Feature-Centric Model for Review Spam Detection (FMRSD) to detect spam reviews. The proposed model examines a wide range of feature sets including ratings, sentiments, content, and users. The experimentation reveals that the proposed technique outperforms the baseline and provides better results.
ScienceON
KISS연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
