Minimizing Social Data Overload through Interest-Based Stream Filtering in a P2P Social Network

2015

Inf Syst Front

Self Cite

Social networking sites (SNSs) have applied personalized filtering to deal with overwhelmingly irrelevant social data. However, due to the focus of accuracy, the personalized filtering often leads to Bthe filter bubble^problem where the users can only receive information that matches their pre-stated preferences but fail to be exposed to new topics. Moreover, these SNSs are black boxes, providing no transparency for the user about how the filtering mechanism decides what is to be shown in the activity stream. As a result, the user's usage experience and trust in the system can decline. This paper presents an interactive method to visualize the personalized filtering in SNSs. The proposed visualization helps to create awareness, explanation, and control of personalized filtering to alleviate the Bfilter bubble^problem and increase the users' trust in the system. Three user evaluations are presented. The results show that users have a good understanding about the filter bubble visualization, and the visualization can increase users' awareness of the filter bubble, understandability of the filtering mechanism and to a feeling of control over the data stream they are seeing. The intuitiveness of the design is overall good, but a context sensitive help is also preferred. Moreover, the visualization can provide users with better usage experience and increase users' trust in the system.

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Section: Proposed Design For Visualizationmentioning

confidence: 99%

Providing awareness, explanation and control of personalized filtering in a social networking site

2015

Inf Syst Front

Self Cite

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“…Having no control or even detailed knowledge about the existing filtering mechanism makes it very hard to make convincing visualizations of the filtered data. That is why we decided to use our own OSN, called MADMICA [28] (available online at http://madmica.usask.ca), an implementation of a privacy-aware decentralized (peer-to-peer) OSN using the Friendica open source framework [29]. MADMICA uses a personalized stream filtering mechanism, developed by Tandukar & Vassileva [30], which was developed and evaluated in a simulation [26].…”

Section: Visualization Designmentioning

confidence: 99%

Understanding and controlling the filter bubble through interactive visualization

Proceedings of the 25th ACM Conference on Hypertext and Social Media

2014

Self Cite

The "filter bubble" is a term which refers to people getting encapsulated in streams of data such as news or social network updates that are personalized to their interests. While people need protection from information overload and maybe prefer to see content they feel familiar or agree with, there is the danger that important issues that should be of concern for everyone will get filtered away and people will lack exposure to different views, living in "echo-chambers", blissfully unaware of the reality. We have proposed a design of an interactive visualization, which provides the user of a social networking site with awareness of the personalization mechanism (the semantics and the source of the content that is filtered away), and with means to control the filtering mechanism. The visualization has been implemented in a peer-to-peer social network, called MADMICA, and we present here the results of a large scale lab study with 163 crowd-sourced participants. The results demonstrate that the visualization leads to increased users' awareness of the filter bubble, understandability of the filtering mechanism and to a feeling of control over their data stream.

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Providing Awareness, Understanding and Control of Personalized Stream Filtering in a P2P Social Network

Lecture Notes in Computer Science

2013