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A Quantitative Look at Cyber-Abuse on Alexandre Sévigny Dept of Communication Studies & Multimedia McMaster University Karin.

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Presentation on theme: "A Quantitative Look at Cyber-Abuse on Alexandre Sévigny Dept of Communication Studies & Multimedia McMaster University Karin."— Presentation transcript:


2 A Quantitative Look at Cyber-Abuse on Alexandre Sévigny Dept of Communication Studies & Multimedia McMaster University Karin Humphreys Dept of Psychology, Neuroscience & Behaviour McMaster University

3 Research Origins - an online current affairs magazine, the first of its kind tried an experiment - allow uncensored anonymous letters commenting on the articles The letter section got nasty and we called to quantitatively look at the letters.

4 Is a good test case? Cyber abuse is a big problem on the internet, but it is hard to gather good data. offers: –Controls on who authors are, letter writers are –a homogenous reader profile … –otherwise, hard to compare compeltely different blogs with each others, etc) –Is subject to a common set of editors

5 Joan Walsh, Ed., “ […] once I joined Salon I started receiving the creepiest personal e-mails about my work. […] But it was hard to know for sure how much had to do with my gender. David Talbot was regularly attacked by wingnuts as a Clinton "butt-boy," so it was impossible to say it was all about my being a woman. It still seems that when a man comes in for abuse online, he's disproportionately attacked as gay […] if he is gay, […] his hate mail at Salon is likely to be […] heavy on sexual imagery and insult, sometimes bordering on violence. Yuck. I couldn't see into anyone else's inbox to be sure if the abuse I was getting was disproportionate, but I suspected it was. Mostly I just ignored it. ”

6 Joan Walsh, cont. “ When Salon automated its letters, ideas that had only seen our in boxes at Salon were suddenly turning up on the site. And I couldn't deny the pattern: Women came in for the cruelest and most graphic criticism and taunting. Gary Kamiya summed it up well in a piece on overall online feedback, noting "an ugly misogynistic aspect" to the reaction to women writers. One thing I noticed early on: We all got nicknames. I'm "Joanie," Rebecca Traister is "Becky," Debra Dickerson is "Debbie" and on and on. There are lots of comments about our looks and sexuality or... likability, to avoid using the f-word, a theme you almost never see even in angry, nasty threads about male writers. Most common is a sneering undercurrent of certainty that the woman in question is just plain stupid; it's hard to believe we have jobs at all. ”Gary Kamiya

7 Joan Walsh, cont. “ I will sound very P.C. saying this (as Bill O'Reilly would be the first to note) but do we just find it easier to bash women?" No, replied one writer: The problem was "the kind of woman writer Salon has been fond of publishing in the last few years... Smug, self-satisfied, without any kind of real difficulty except their sad inability to make the rest of the world understand, and so appreciate, them for who they are," and then he went on to name a lot of us. Glad we cleared that up. ”

8 Greater Internet Jerk Theory Normal Person + Anonymity + Audience = A TOTAL JERK

9 Screenshot

10 Article Screen

11 Letters Entry Section

12 Research Questions Is gender of magazine author a significant variable in the cyber abuse contained in the letters? How does cyber abuse of female writers differ from abuse of male writers?

13 Method: Sourcing Sourced letters from “News & Politics” and “Opinions” sections Took letters written after’s new “verification” policy Explicitly excluded articles that dealt with gender issues One article per writer per month (to get max. # of unique writers)

14 Method: Sorting Ideas-critique –disagree with ideas –no ref to “this author says…” Author/article critique: –positive, negative, in-between –one example of every unique author, randomly selected amongst them –number of letters indicator of degree of controversy

15 Our Mini-Codebook Reference: author, article, salon, full name, first name, last name, nickname, Mr./Ms./Dr., you/he/she, fullname-other Address: to author, to salon, other letter writers Subject: just about ideas, ad hominen attack, ad hominem praise Qualifying-but: “ I love Camille Pagilia's editorials. However, she is still spouting the old Vietnam War histories. ” Vitriol: “ I'll remember how I am treated by you women the next time a woman asks me to listen to her opinion on anything. ”

16 There were real trends in the data Cyber Abuse seemed to differ along several vectors FemaleMale 59.0558.75

17 Total9.603.74 News5.501.96 Opinion15.754.67

18 Total0.140.07 News0.090.04 Opinion0.210.09






24 Mr/Ms.0.0020.16 First Name0.0180.011

25 Summary of (prelim.) Results There were the same number of letters to articles written by both genders. There were both a higher number and greater proportion of negative letters to articles written by female writers. Female writers are proportionally more often addressed in a more familiar way. Female writers receive a greater proportion of personal letters than male writers.

26 Availability Heuristic Some people generalize, saying “everybody gets abused on the internet, not predominantly women” because they have seen specific examples of both types of abuse. So, is it just that women are more sensitive, and think they are being abused more? Empiricism: the only way to know is to actually count so that we can fix the situation

27 So maybe we should ask...

28 Bill O’Reilly’s research question… “So hard to say, maybe the women's articles are just all poorer than the men’s and attract more criticism?”

29 We have an answer, Bill. And we are starting to have the data that demonstrates that you’re wrong. Empirical research will succeed where cultural studies and critical theory have abjectly failed. It’s easy to pooh-pooh a critical opinion or theory but It’s hard to disagree with the facts.

30 Future Directions This is a preliminary look into the data We are drilling down deeper and conducting more sophisticated analyses to understand the linguistic nature of the abuse Comparing abuse pre-validation and post- validation

31 Thanks to the team at the Cognitive Science Laboratory McMaster University Thanks to you for listening.

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