اندازه گیری ها در رسانه های اجتماعی
ترجمه نشده

اندازه گیری ها در رسانه های اجتماعی

عنوان فارسی مقاله: توجه تصادفی: مقایسه اندازه گیری های دیداری، پایان پذیر و بی انتهای توجه در رسانه های اجتماعی
عنوان انگلیسی مقاله: Accidentally Attentive:Comparing visual, close-ended, and open-ended measures of attention on social media
مجله/کنفرانس: نقش کامپیوتر در رفتار انسان – Computers in Human Behavior
رشته های تحصیلی مرتبط: مهندسی فناوری اطلاعات
گرایش های تحصیلی مرتبط: اینترنت و شبکه های گسترده
کلمات کلیدی فارسی: گرایش اندازه گیری، اندازه گیری های خود گزارش، رسانه های اجتماعی، ارائه انتخابی، ارائه تصادفی
کلمات کلیدی انگلیسی: Measurement bias، Self-report measures، Social media، Selective exposure، Incidental exposure
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.chb.2019.05.017
دانشگاه: Hubbard School of Journalism, University of Minnesota, 111 Murphy Hall, Minneapolis, MN 55455 USA
صفحات مقاله انگلیسی: 10
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2019
ایمپکت فاکتور: 5.876 در سال 2018
شاخص H_index: 137 در سال 2019
شاخص SJR: 1.711 در سال 2018
شناسه ISSN: 0747-5632
شاخص Quartile (چارک): Q1 در سال 2018
فرمت مقاله انگلیسی: PDF
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E13650
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست مطالب (انگلیسی)

Abstract

1. Introduction

2. Methods and measures

3. Results

4. Discussion

Acknowledgements

Appendix A. Supplementary data

References

بخشی از مقاله (انگلیسی)

Abstract

The question of how to measure exposure to different types of content on social media grows in importance with increased use of these platforms. Social media further complicate this task by bringing diverse content into the same space, raising the question of whether selective exposure or incidental exposure theories best explain attention patterns. We contribute to this debate in two ways. First, we test how well visual attention aligns with expressed content preferences to understand attention online. Second, we compare visual attention to diverse social media content to two types of self-reported measures of recalled attention to content – close-ended versus open-ended – to examine how best to measure attention. Using eye tracking, we demonstrate that visual attention to social, news, and political posts is not associated with interest in those topics, suggesting attention to content seen incidentally on social media is quite high. Second, we find that visual attention to social and political (but not news) posts relates to close-ended self-reported measures of recalled attention, but visual attention is associated with open-ended recalled attention only for political posts. We propose that researchers need to go beyond measures of exposure and carefully consider how best to measure attention to social media content.

Introduction

Social media have exploded over the last decade, rapidly becoming a dominant form of communication. They can serve as a source of news and information, an opportunity to connect with friends and peers, or a space in which individuals produce and share their own content (Pew, 2015). As social media use grows, it is of increasing importance to understand how people spend their time while engaged with social media—are they engaging with political content? Watching cat videos? Keeping up with their community? Because the answers to these questions affects people’s knowledge and behaviors (Bode, 2016a; Boulianne, 2015; Gil de Zúñiga, Jung, & Valenzuela, 2012), it therefore also matters that researchers are confident in the measures they use to determine who is paying attention to diverse content on social media, and whether users can report such exposure accurately. This study integrates work from cognitive psychology, media psychology, and journalism to address the important question of attention to content, as well as the methodological question of measuring such attention via self-reports. Two theoretical frameworks can be used to explain the types of content that garner attention on social media. According to the incidental exposure framework, the intersection of different forces – choices by an individual but also by a diverse social network, strategic actors, and algorithmic curation – offer new opportunities for people to encounter otherwise-avoided topics and perspectives (Bode, 2016a; Kim, Chen, & Gil; de Zuñiga, 2013; Thorson & Wells, 2015; Vraga, Bode, & Troller-Renfree, 2016b). In contrast, the selective exposure framework would suggest that social media represent one more place where individuals can deliberately select information according to their preferences, which are then reinforced by social media companies attempting to maintain attention (Bakshy, Messing, & Adamic, 2015; Pariser, 2012).