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To qualitative researchers, social media offers a novel opportunity to harvest a massive and diverse range of content without the need for intrusive or intensive data collection procedures. However, performing a qualitative analysis across a massive social media data set is cumbersome and impractical. Instead, researchers often extract a subset of content to analyze, but a framework to facilitate...
Interactions among tweets, i.e., mentions, retweets, replies, are important factors contributing to the quality of topic derivation on Twitter. If applied correctly, the incorporation of tweet interactions can significantly improve the quality of topic derivation in comparison with approaches that are mainly based on the content similarity analysis. However, how interactions can be measured and integrated...
Twitter has become one of the most popular social media platforms, widely used for discussion and information dissemination on all kinds of topics. As a result, both business and academics have researched methods to identify the topics being discussed on Twitter. Those methods can be employed for a number of applications, including emergency management, advertisements, and corporate/government communication...
The aim of this study was to determine the effect of e-marketing and e-service quality on e-satisfaction and its impact on e-loyalty. This research was conducted on customers in Jakarta. Data were collected from a sample of 100 respondents. The data were analyzed using path analysis. The result of this study found that e-marketing did not affect the e-satisfaction. E-marketing and e-service quality...
The Gregg and Walczak definition about e-image has been inspired us to examine their theoretical model in a different digital marketplace environment. As a novelty, we introduced the Real-Time Support Assistance (RTOSA) concept as a supplementary moderating variable. This paper constitutes hypothetical development about the proposed RTOSA and contains a brief description of Indonesia largest online...
Amongst all the social media platforms available, Twitter is rapidly becoming the main one used for communications about real-time events. As a result, there is a lot of interest in monitoring Twitter and understanding the topics of conversations. However, the fact that tweets are short in content makes topics derivation a challenge, as most existing methods use content features only, sometimes integrated...
Twitter as a big data social network becomes one of the most important sources for capturing the up-to-date events happening in the world. Topic derivation from Twitter is important for various applications such as situation awareness, market analysis, content filtering, and recommendations. However, tweets are short messages, which makes topic derivation challenging. Current methods employ various...
In this paper, we present a novel method in making recommendations by leveraging Tie Strength, an integrated social relationship measurement calculated from various user information gathered from social media. Moreover, the proposed method adopts Least Absolute Errors in factorization scheme to reduce the sensitivity to data outliers. We have conducted comprehensive experiments over the real datasets...
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