کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6861092 | 1438979 | 2015 | 27 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Human content filtering in Twitter: The influence of metadata
ترجمه فارسی عنوان
فیلتر کردن محتوای محتوا در توییتر: تاثیر متادیتا
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کلمات کلیدی
تصمیم سازی، توییتر، متاداده، نشانه، به رسمیت شناختن،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
In this research we have conducted an open online experiment in which participants are shown quantitative and qualitative meta-data describing two pieces of Twitter content. Without revealing the text of the tweet, participants are asked to make a selection. We observe the decisions made from 239 surveys and discover insights into human behaviour on decision making for content selection. We find that for qualitative meta-data consumption decisions are driven by online friendship and for quantitative meta-data the largest numerical value presented influences choice. Overall, the 'number of retweets' is found to be the most influential quantitative meta-data, while displaying multiple cues about an author׳s identity provides the strongest qualitative meta-data. When both quantitative and qualitative meta-data is presented, it is the qualitative meta-data (friendship information) that drives selection. The results are consistent with application of the Recognition heuristic, which postulates that when faced with constrained decision-making, humans will tend to exercise judgement based on cues representing familiarity. These findings are useful for future interface design for content filtering and recommendation systems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Human-Computer Studies - Volume 74, February 2015, Pages 32-40
Journal: International Journal of Human-Computer Studies - Volume 74, February 2015, Pages 32-40
نویسندگان
Martin J. Chorley, Gualtiero B. Colombo, Stuart M. Allen, Roger M. Whitaker,