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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Takoulidou, E. Chorianopoulos, K. |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Inf., Ionian Univ., Corfu, Greece (Takoulidou, E.; Chorianopoulos, K.) |
| Abstract | The need for more experimental data, but also quicker and cheaper, lead us beyond traditional lab experiments, approaching a new subject pool via a crowdsourcing platform. SocialSkip is an open system that leverages the video clickstream data for extracting useful information about the video content and the viewers. The difficulty of embedding a pre-existing system as a task demands a carefully designed interface, adjusting experiments and be aware of workers' cheating behavior. We present a replicable task design and by analyzing crowdsourced results, we highlight problems in experimental procedure and propose potential solutions for future crowdsourcing experiments. The proposed crowdsourcing methodology achieved the collection of a significant amount of video clickstream data, in a timely manner and with affordable cost. Our findings indicate that future social media analytics systems should include an integrated crowdsourcing module. Further research should focus on collecting more data by controlling the random worker behavior a priori. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 535443 |
| Page Count | 5 |
| File Format | |
| e-ISBN | 9781467393119 |
| DOI | 10.1109/IISA.2015.7387979 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-07-06 |
| Publisher Place | Greece |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Crowdsourcing Google Quality control Media User Experiment Data mining Web Video YouTube |
| Content Type | Text |
| Resource Type | Article |
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