An Information Diffusion Based Recommendation Framework for Micro-Blogging

Cheng, Jiesi; Sun, Aaron; Hu, Daning; Zeng, Daniel

doi:10.2139/ssrn.1713486

Cited by 13 publications

(10 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In an attempt to filter real time news/updates from irrelevant personal messages and spam, Cheng et al (2011) propose analysis of information diffusion patterns for a large set of micro-blogs that update emergency news. They claim that their approach (using Twitter data) outperforms other benchmark solutions to offer diverse user preferences and customized results during critical events.…”

Section: Role Of Social Media During Critical/extreme Eventsmentioning

confidence: 99%

“…identify the lack of conceptualization in the notion of technology addiction; they recognize that the process of defining it is still in the early stages, and is being debated across communities. For researchers interested in examining aspects of Twitter, Cheng et al (2011) recommend incorporating the location metric focused on Twitter's geo location feature allowing users to trace the latitude and longitude of Tweets. Another recommendation for Twitter related studies comes from Benthaus et al (2016), where they suggest researchers should study user involvement differently, based on how often users choose to 'like' the content of a company.…”

Section: Limitations and Future Research Directionsmentioning

confidence: 99%

See 1 more Smart Citation

Advances in Social Media Research: Past, Present and Future

et al. 2017

View full text Add to dashboard Cite

Social media comprises communication websites that facilitate relationship forming between users from diverse backgrounds, resulting in a rich social structure. User generated content encourages inquiry and decision-making. Given the relevance of social media to various stakeholders, it has received significant attention from researchers of various fields, including information systems. There exists no comprehensive review that integrates and synthesises the findings of literature on social media. This study discusses the findings of 132 papers (in selected IS journals) on social media and social networking published between 1997 and 2017. Most papers reviewed here examine the behavioural side of social media, investigate the aspect of reviews and recommendations, and study its integration for organizational purposes. Furthermore, many studies have investigated the viability of online communities/social media as a marketing medium, while others have explored various aspects of social media, including the risks associated with its use, the value that it creates, and the negative stigma attached to it within workplaces. The use of social media for information sharing during critical events as well as for seeking and/ or rendering help has also been investigated in prior research. Other contexts include political and public administration, and the comparison between traditional and social media. Overall, our study identifies multiple emergent themes in the existing corpus, thereby furthering our understanding of advances in social media research. The integrated view of the extant literature that our study presents can help avoid duplication by future researchers, whilst offering fruitful lines of enquiry to help shape research for this emerging field.

show abstract

Section: Role Of Social Media During Critical/extreme Eventsmentioning

confidence: 99%

Section: Limitations and Future Research Directionsmentioning

confidence: 99%

Advances in Social Media Research: Past, Present and Future

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Most studies have positioned social media as a channel in tapping the knowledge, capital, and collective strength of community (e.g., Cheng, Sun, Hu, & Zeng, 2011;Gao et al, 2011;Hui, Tyshchuk, Wallace, Magdon-Ismail, & Goldberg, 2012). For example, Gao et al (2011) focus on the information propagating capability of social media to gather and integrate data from the community.…”

Section: Introductionmentioning

confidence: 99%

“…This is an exemplar of crowdsourcing in generating collective intelligence. At the same time, the information flow in social media has been studied in great detail: Hui et al (2012) and Cheng et al (2011) examine the information-diffusion pattern in social media to better extract useful information for crisis response effectiveness. Moreover, Oh, Agrawal, Rao (2013) and Oh, Kwon, and Raghav (2010), adopting the perspective of informational analysis, present the duality of social media in rumor and informational convergence.…”

Section: Introductionmentioning

confidence: 99%

ICT-Enabled Community Empowerment in Crisis Response: Social Media in Thailand Flooding 2011

Leong¹,

Pan²,

Ractham³

et al. 2015

JAIS

113

View full text Add to dashboard Cite

show abstract

“…To address this problem, passive filtration approaches, such as search engines, have been used as a fundamental technique to screen useful information [1,5]. To further improve user experiences and reflect personalization of individual users, various recommender systems have also been proposed recently in an active way towards personalized nomination of resources and to assist individuals for efficiently identifying their potential interest, leading to a variety of successful stories in the online recommendations of books [18], movies [23], news [26], TV programs [4], microblogs [29] and many others [2,7,30].…”

Section: Introductionmentioning

confidence: 99%

TAFFY: incorporating tag information into a diffusion process for personalized recommendations

Gan

2015

World Wide Web

View full text Add to dashboard Cite

The last few years have witnessed an explosion of information caused by the exponential growth of the Internet and World Wide Web, which confronted us with information overload and brought about an era of big data, appealing for efficient personalized recommender systems to assist the screening of useful information from various sources. As for a recommender system with more than the fundamental object-user rating information, such accessorial information as tags can be exploited and integrated into final ranking lists to improve recommendation performance. However, although existing studies have demonstrated that tags, as the additional yet useful resource, can be designed to improve recommendation performance, most network-based approaches take users, objects and tags as two bipartite graphs, or a tripartite graph, and therefore overlook either the important information among homogeneous nodes in each sub-graph, or the bipartite relations between users, objects or tags. Moreover, recent studies have suggested that the filtration of weak relationships in networks may reasonably enhance recommendation performance of collaborative filtering methods, and it has also been demonstrated that approaches based on the diffusion processes could more effectively capture relationships between objects and users, hence exhibiting higher performance than a typical collaborative filtering method. Based on these understandings, we propose a data fusion approach that integrates historical and tag data towards personalized recommendations. Our method coverts historical and tag data into complex networks, resorts to a diffusion kernel to measure the strength of associations between users and objects, and adopts Fisher's combined probability test to obtain the statistical significance of such associations for personalized recommendations. We validate our approach via 10-fold cross-validation experiments. Results show that our method outperforms existing methods in World Wide Web not only the recommendation accuracy and diversity, but also retrieval performance. We further show the robustness of our method to related parameters.

show abstract

An Information Diffusion Based Recommendation Framework for Micro-Blogging

Cited by 13 publications

References 26 publications

Advances in Social Media Research: Past, Present and Future

Advances in Social Media Research: Past, Present and Future

ICT-Enabled Community Empowerment in Crisis Response: Social Media in Thailand Flooding 2011

TAFFY: incorporating tag information into a diffusion process for personalized recommendations

Contact Info

Product

Resources

About