新闻传播5大具体领域引用量最高的15篇论文清单(附下载方式) Part1 Algorithms and society(1)Ananny, M., & Crawford, K. (2018). Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability. New Media & Society, 20(3), 973–989. https://doi.org/10.1177/1461444816676645(2)Diakopoulos, N., & Koliska, M. (2017). Algorithmic transparency in the news media. Digital Journalism, 5(7), 809–828. https://doi.org/10.1080/21670811.2016.1208053(3)Haim, M., Graefe, A., & Brosius, H.-B. (2018). Burst of the filter bubble? Digital Journalism, 6(3), 330–343. https://doi.org/10.1080/21670811.2017.1338145Part2 Information consumption(1)Fletcher, R., & Park, S. (2017). The impact of trust in the news media on online news consumption and participation. Digital Journalism, 5(10), 1281–1299. (2)Shin, J., & Thorson, K. (2017). Partisan selective sharing: The biased diffusion of fact-checking messages on social media. Journal of Communication, 67(2), 233–255. (3)Toff, B., & Nielsen, R. K. (2018). “I Just Google It”: Folk theories of distributed discovery. Journal of Communication, 68(3), 636–657. Part3 Advertising(1)Boerman, S. C., Kruikemeier, S., & Zuiderveen Borgesius, F. J. (2017). Online behavioral advertising: A literature review and research agenda. Journal of Advertising, 46(3), 363–376. (2)Voorveld, H. A. M., van Noort, G., Muntinga, D. G., & Bronner, F. (2018). Engagement with Social Media and Social Media Advertising: The Differentiating Role of Platform Type. Journal of Advertising, 47(1), 38–54. (3)Liu, X., Burns, A. C., & Hou, Y. (2017). An Investigation of brand-related user-generated content on Twitter. Journal of Advertising, 46(2), 236–247. Part4 Social Media(1)Anspach, N. M. (2017). The new personal influence: How our Facebook friends influence the news we read. Political Communication, 34(4), 590–606. (2)Valenzuela, S., Correa, T., & Zúñiga, H. G. de. (2018). Ties, likes, and tweets: Using strong and weak ties to explain differences in protest participation across Facebook and Twitter use. Political Communication, 35(1), 117–134. (3)Margolin, D. B., Hannak, A., & Weber, I. (2018). Political fact-checking on Twitter: When do corrections have an effect? Political Communication, 35(2), 196–219. https://doi.org/10.1080/10584609.2017.1334018 Part5 Affordances and personalities(1)Evans, S. K., Pearce, K. E., Vitak, J., & Treem, J. W. (2017). Explicating affordances: A conceptual framework for understanding affordances in communication research. Journal of Computer-Mediated Communication, 22(1), 35–52. (2)Liu, D., Baumeister, R. F., Yang, C.-C., & Hu, B. (2019). Digital communication media use and psychological well-being: A meta-analysis. Journal of Computer-Mediated Communication, 24(5), 259-273.(3)Bol, N., Dienlin, T., Kruikemeier, S., Sax, M., Boerman, S. C., Strycharz, J., Helberger, N., & de Vreese, C. H. (2018). Understanding the effects of personalization as a privacy calculus: Analyzing self-disclosure across health, news, and commerce contexts†. Journal of Computer-Mediated Communication, 23(6), 370–388. 那么如何获取并精读、理解和掌握这15篇高质量高被引的论文呢?答案是:报名参加【新闻传播学英文文献精读营】 论文资料包已经上传到精读营课程的附件资料包内(如下图),大家购买课程报名后可以按照【新传课程—精读营—相关资料下载】路径提前下载进行阅读,课程开始后,领读老师会带着大家进行详细的论文拆解。 课程名称 新闻传播学英文文献精读营 主讲嘉宾 一念博士国际Top100院校传播学博士在读。她的研究探讨人、科技以及社会的相互作用。她用跨学科的思维以及计算传播方法研究情绪与认知在技术接受方面的作用。她目前的工作集中在新闻推荐系统中的serendipidy(运气)、information overload(信息过载)以及fake news diffusion(假新闻传播)。发表SSC论文和国际顶级会议论文多篇。 课程特色 01 拥有海外名校传播学学习和科研经历的专业主讲老师为大家甄选15篇该领域引用最高的文献02 5次课程5个专题全程详细为大家拆解新闻传播学高水平英文论文的阅读技巧和写作思路以供借鉴03 帮助大家高效学习读文献,让所有想要读英文文献的新传师生不再止步不前,提高科研发表水平 课程时间 2022年10月28日—2022年11月25日(已更新完毕,即领即学) 课程学员 面向新闻传播学以及广大人文社会科学领域的师生开放报名方式付费听课 扫描上方二维码,直接付费购买即可 论文资料包已经上传到精读营课程的附件资料包内,大家购买课程报名后可以按照【新传课程—精读营—相关资料下载】路径提前下载进行阅读,课程开始后,领读老师会带着大家进行详细的论文拆解。