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Ye Sun
@YeSun_comm
Retweet =\= endorsement Comm scholar @ City University of Hong Kong

Ye Sun’s Tweets

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How well have communication meta-analysts done in addressing publication bias? Well, not too well.😉 See my review paper w/ Zhongdang Pan (UW-Madison) to appear in the HCR special issue with findings from 45 meta-analyses in 6 comm journals (2005-18) ⬇️
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Couldn't have had a better time in Vienna . Thanks, Tobias , for being a superb host! Greatly enjoyed our walks, meals, and conversations. The honor and privilege were mine. 🤗
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This week we had two special guests @IPKW_univie: @YeSun_comm was our Lazarsfeld guest prof, with a class on meta-analyses & a talk on Comm as a science. Kevin DeLuca gave a talk on Media effects on society. What a privilege to spent time together with such insightful experts! 🙏
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It was a great pleasure to share my work with you all there . Thank you for the summary. I looked enthusiastic with my hand gestures 😁.
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"How Scientific is Communication Science?" In today's talk, @YeSun_comm addressed this Q focusing on statistical power in experiments. Result: 1⃣ Only ~5% report a priori power analyses 2⃣ Power for small/medium effects only ~50% 3⃣ But: Average power is increasing in the field!
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Just happy we all survived it happily 😄🥳. Also wish that meta-analysis could be taught more regularly.
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Took a 5-day, 5h/day doctoral meta-analysis class run by @YeSun_comm. One of the best courses I've ever taken and omg I wish meta-analysis was taught regularly. Why isnt't it??? twitter.com/YeSun_comm/sta…
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What an honor. So appreciated. Now have to work on the slides to earn my Christmas market punch 😀.
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Next Monday, our current Lazarsfeld-guest professor @YeSun_comm will present a talk on "How scientific is Communication?" Very much looking forward, everyone invited!
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A must read if you are interested in TPP/TPE research 👉
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In a new @Journal_Of_Comm I argue a lot of what we think we know about the third-person effect is probably wrong. The standard measure is flawed. This warps the conclusions we've drawn about its extent, correlates, and downstream "effects" academic.oup.com/joc/advance-ar
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Happy to see 's #CMM doing so well, and proud to serve as an associate editor with EiC LJ Shen and fellow AE . Check out (and cite!) our latest articles here (tandfonline.com/action/showAxa) and submit your methods work. Happy to answer any questions.
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These are the 5 y IF's for Communication (updated w the 2021 scores). Top 5: 1. JCMC @ica_jcmc 2. Journal of Advertising 3. Communication Methods & Measures 4. Journal of Communication @Journal_Of_Comm 5. Political Communication @polcommjournal 2/4
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Re-reading a review that led to a rejection of a manuscript a year ago. Now that my defensiveness is all gone, I so appreciate all the criticism--thoughtful & helping to elevate the work to a higher level that I didn't see. Like p-value, there's more to a dichotomous decision.
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Entirely agree! 😀
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Brace for results of content analysis of 5 top journals in past 20 years by Ye Sun. Large majority of studies doesnt report any power analysis. Most studies (80%) are underpowered to reliably detect a modest effect. Editors, reviewers and authors, we need to do better #ica22
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Can't make it to Paris but our second author Lijiang Shen is there to present it. Sorry to miss the great session but hope everyone there is enjoying it!
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Happening now, the @ICA_CSaB top paper panel! Join us in the Hyatt Regency 12+14. Or, find the livestream link on the Cadmore platform! #ica22
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🥳Announcing MERIT (Meta-Evaluation and Research Integration Team) as a new research initiative to promote meta-level research! Starting with a few colleagues who share interest in meta-analyses, systematic reviews, and other evidence synthesis/evaluation methods.
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We're currently preparing a qualitative study on #openscience in Mass Comm. We aim to be as inclusive, reflexive, and open as possible, so: Please give feedback! Please collaborate! Please share!
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Hey #openscience scholars: @tdienlin and I are conducting a qualitative study of mass comm scholars on the motivations/deterrents to open science research. Would love your feedback on our questionairre if you have any thoughts or suggestions! docs.google.com/document/d/1zl
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Concluding thoughts: 1. It's important critically to engage with research. In a fair & constructive way. I hope & believe our comment is fair & constructive. 2. Let's be more open to critical discussions of research. Please criticize my research & this comment. Because 👇 13/13
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Great thread by on questions & answers about #openscience in qualitative research. ⬇️ #Openscience is about improving transparency about research processes and hence the rigor of science. Qual vs. quant scholars tackle diff. issues, but toward the same overarching goal.
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Okay, #ica20, let's do this. Here are my thoughts on #openscience and #opencomm for the more qualitative approaches in our field! (Beware, long thread.) (Also, please be kind.)
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What a great list!
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absence of evidence ≠ evidence of absence measurement error ≠ bias towards null clinical trial ≠ study with patients multivariate ≠ multivariable 95%CI ≠ 95% probability p-value ≠ probability H0 correlation ≠ causation significant ≠ relevant bias ≠ error odds ≠ risk
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"Stats is hard." We all struggle at diff. levels and there's always so much to learn. It's okay not to know, but I'm trying my best not to be the person who "doesn’t know that he doesn’t know" and "thinks that he knows what he’s talking about when he doesn’t." Never-ending work.
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So much of academia is about connections and reputation laundering statmodeling.stat.columbia.edu/2020/05/14/so-
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Over the course of my career, I have been an Associate Editor at three journals. Finding reviewers was one of the most difficult parts of the job. Today is the fifth anniversary of the funniest "decline to review" notes I received. I post it below for your reading please. 1/4
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Do you remember when you joined Twitter? I do! #MyTwitterAnniversary --Twitter asked me to celebrate my 1 year anniversary. I guess, why not...? Anything that can be celebrated nowadays should be, right? 🥳 Here is to my 1⃣ year on Twitter with 1⃣0⃣0⃣ followers!😅💯
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Service announcement: Hot research topics (= Corona virus) + motivated reasoning (= Wanting to help) + selective reporting of what 'works' + potential real life implications of single studies means all you Corona researchers need LOWER your alpha levels substantially.
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Amazing to see "rise up against statistical significance" backfiring (or, to be fair, being misunderstood) so badly. And it's just a paper about the coronavirus, so it's not like it MATTERS or anything... preprints.org/manuscript/202
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Others are biased. I am not.
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I'm less biased than you, and I have fewer shortcomings. Bias blind spot replicates; not everything's broken. Also, the more you believe in Free Will, the fewer personal shortcomings you think you have. from @giladfeldman researchgate.net/publication/33
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