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Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
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- Twitter (12)
- Social media (4)
- Social network (3)
- User behavior (3)
- Virality (3)
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- Feature extraction (2)
- Information propagation (2)
- Machine learning (2)
- Micro-blogging (2)
- Microblogging (2)
- Networking behavior (2)
- Susceptibility (2)
- Acoustic content (1)
- Adoption dynamics (1)
- And online friendship (1)
- Audience segmentation (1)
- Blended learning (1)
- Bot profiling (1)
- Brand factors (1)
- Burst topic (1)
- Cheating (1)
- Classification (1)
- Community detection (1)
- Community pacemakers (1)
- Consumer finance (1)
- Content propagation (1)
- Crisis (1)
- Crisis Communication (1)
- Customer relationship management (1)
- Data mining (1)
- Publication
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Articles 31 - 38 of 38
Full-Text Articles in Social and Behavioral Sciences
Learning To Find Topic Experts In Twitter Via Different Relations, Wei Wei, Gao Cong, Chunyan Miao, Feida Zhu, Guohui Li
Learning To Find Topic Experts In Twitter Via Different Relations, Wei Wei, Gao Cong, Chunyan Miao, Feida Zhu, Guohui Li
Research Collection School Of Computing and Information Systems
Expert finding has become a hot topic along with the flourishing of social networks, such as micro-blogging services like Twitter. Finding experts in Twitter is an important problem because tweets from experts are valuable sources that carry rich information (e.g., trends) in various domains. However, previous methods cannot be directly applied to Twitter expert finding problem. Recently, several attempts use the relations among users and Twitter Lists for expert finding. Nevertheless, these approaches only partially utilize such relations. To this end, we develop a probabilistic method to jointly exploit three types of relations (i.e., follower relation, user-list relation and list-list …
Ranking Of High-Value Social Audiences On Twitter, Siaw Ling Lo, Raymond Chiong, David Cornforth
Ranking Of High-Value Social Audiences On Twitter, Siaw Ling Lo, Raymond Chiong, David Cornforth
Research Collection School Of Computing and Information Systems
Even though social media offers plenty of business opportunities, for a company to identify the right audience from the massive amount of social media data is highly challenging given finite resources and marketing budgets. In this paper, we present a ranking mechanism that is capable of identifying the top-k social audience members on Twitter based on an index. Data from three different Twitter business account owners were used in our experiments to validate this ranking mechanism. The results show that the index developed using a combination of semi-supervised and supervised learning methods is indeed generic enough to retrieve relevant audience …
Getting People To Buy, Always, Singapore Management University
Getting People To Buy, Always, Singapore Management University
Perspectives@SMU
Creating touchpoints in stores and embracing the social media world keep consumers engaged with brands
Investigating The Influence Of Offline Friendship On Twitter Networking Behaviors, Young Soo Kim, Felicia Natali, Feida Zhu, Ee-Peng Lim
Investigating The Influence Of Offline Friendship On Twitter Networking Behaviors, Young Soo Kim, Felicia Natali, Feida Zhu, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
We investigate the influence of offline friendship in three specific areas of Twitter networking behaviors: (a) network structure, (b) Twitter content and (c) interaction on Twitter. We observe some interesting findings through the empirical analysis of 2193 pairs of users who are online friends. When these pairs of users know each other offline, they are more likely to (1) respond to the online gesture of friendship from their friend, (2) share mutual online friends, (3) distribute and gather information in their friend’s Twitter network, (4) pay attention to their friend’s tweets, (5) post tweets that might be of interest to …
Posting Topics ≠ Reading Topics: On Discovering Posting And Reading Topics In Social Media, Wei Gong, Ee-Peng Lim, Feida Zhu
Posting Topics ≠ Reading Topics: On Discovering Posting And Reading Topics In Social Media, Wei Gong, Ee-Peng Lim, Feida Zhu
Research Collection School Of Computing and Information Systems
Social media users make decisions about what content to post and read. As posted content is often visible to others, users are likely to impose self-censorship when deciding what content to post. On the other hand, such a concern may not apply to reading social media content. As a result, the topics of content that a user posted and read can be different and this has major implications to the applications that require personalization. To better determine and profile social media users’ topic interests, we conduct a user survey in Twitter. In this survey, participants chose the topics they like …
Friendship Maintenance And Prediction In Multiple Social Networks, Roy Ka-Wei Lee, Ee-Peng Lim
Friendship Maintenance And Prediction In Multiple Social Networks, Roy Ka-Wei Lee, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Due to the proliferation of online social networks (OSNs), users find themselves participating in multiple OSNs. These users leave their activity traces as they maintain friendships and interact with other users in these OSNs. In this work, we analyze how users maintain friendship in multiple OSNs by studying users who have accounts in both Twitter and Instagram. Specifically, we study the similarity of a user's friendship and the evenness of friendship distribution in multiple OSNs. Our study shows that most users in Twitter and Instagram prefer to maintain different friendships in the two OSNs, keeping only a small clique of …
On Analyzing Geotagged Tweets For Location-Based Patterns, Philips Kokoh Prasetyo, Palakorn Achananuparp, Ee Peng Lim
On Analyzing Geotagged Tweets For Location-Based Patterns, Philips Kokoh Prasetyo, Palakorn Achananuparp, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Geotagged social media is becoming highly popular as social media access is now made very easy through a wide range of mobile apps which automatically detect and augment social media posts with geo-locations. In this paper, we analyze two kinds of location-based patterns. The first is the association between location attributes and the locations of user tweets. The second is location association pattern which comprises a pair of locations that are co-visited by users. We demonstrate that through tracking the Twitter data of Singapore-based users, we are able to reveal association between users tweeting from school locations and the school …
A Comparison Of Fundamental Network Formation Principles Between Offline And Online Friends On Twitter, Felicia Natali, Feida Zhu
A Comparison Of Fundamental Network Formation Principles Between Offline And Online Friends On Twitter, Felicia Natali, Feida Zhu
Research Collection School Of Computing and Information Systems
We investigate the differences between how some of the fundamental principles of network formation apply among offline friends and how they apply among online friends on Twitter. We consider three fundamental principles of network formation proposed by Schaefer et al.: reciprocity, popularity, and triadic closure. Overall, we discover that these principles mainly apply to offline friends on Twitter. Based on how these principles apply to offline versus online friends, we formulate rules to predict offline friendship on Twitter. We compare our algorithm with popular machine learning algorithms and Xiewei’s random walk algorithm. Our algorithm beats the machine learning algorithms on …