نوع مقاله : علمی ـ پژوهشی

نویسندگان

1 دانشگاه تهران

2 دانشگاه آزاد اسلامی- واحد تهران مرکز

چکیده

توئیتر در حال حاضر به یکی از رسانه های اصلی برای کنشگری در جریان رویدادهای سیاسی تبدیل شده است. در این تحقیق، با تمرکز بر مفهوم همگان شبکه ای تلاش می کنیم تا چگونگی کنشگری این همگان ها در توئیتر فارسی را در جریان انتخابات ریاست جمهوری سال 1396 مطالعه کنیم. برای انجام اینکار، نوع توئیت های تولید شده، لحن توئیت ها و همچنین قالب بندی شخصیت ها در توئیتر فارسی را تحلیل می کنیم. داده های تحقیق (دو میلیون و 596 هزار و 284 توئیت) در دوران انتخابات با روش گلوله برفی و استفاده از 94 کلیدواژه و هشتگ، از API توئیتر گردآوری شد و ما با انتخاب 10416 توئیت از 50 کاربر موثر در هر همگان شبکه ای، تلاش کردیم به پرسشهای تحقیق پاسخ دهیم. رویکرد تحلیلی تحقیق نیز ترکیبی از روش تحلیل محتوای مردمنگارانه و تحلیل گفتمان انتقادی رسانه های اجتماعی بود. نتایج تحقیق نشان داد تفسیر، نقل قول و خبر پربسامدترین انواع توئیت در توئیتر فارسی هستند. همچنین، لحن جدی و کنایی در همگان های شبکه ای بسامد بیشتری دارد. یافته ها همچنین نشان داد که منازعه اصلی در توئیتر فارسی بین توئیت های حمایتی اصلاح طلبان و انتقادی اصولگرایان در مورد روحانی شکل گرفته است.

کلیدواژه‌ها

عنوان مقاله [English]

Decoding networked publics on Persian Twitter: Tweet type, tone and orientation to characters in Iran 2017 presidential election

نویسندگان [English]

  • Hossein Kermani 1
  • Fatemeh Rasouli 2
  • zahra majdizade 1

1 University of Tehran

2 Islamic Azad University, Center Tehran Branch

چکیده [English]

This research sheds light on networked publics’ activism on Persian Twitter. Networked publics is a phenomena to understand dynamics and practices of social media users. Based on this concept and networked framing theory, we investigated tweet types, tweet tones and the ways of framing characters (and tweet orientation toward them) by networked publics on Persian Twitter during Iran 2017 presidential election. We combined social network analysis, ethnographic content analysis and social media critical discourse study approach. First, we collected 2596284 tweets during the election period. Then, we focused on retweet (RT) network as the information diffusion network, and discovered networked publics by applying cluster analysis on this corpus. Afterwards, we identified 50 top influential users in each cluster based on their PageRanks. Finally, we collected all tweets of these users in the whole network and analyzed them. We used 3 coders to code the selected sample of 10416 tweets in 3 rounds. Results showed that commentary, quotation and news are the most frequent tweet types. Furthermore, Iranian users mostly tweeted using serious and sarcastic tones. Finally, our finding showed that Rouhani was the first name in framed characters.

کلیدواژه‌ها [English]

  • Twitter
  • Networked publics
  • Iran
  • Social media
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