{"id":1572,"date":"2022-11-23T13:46:03","date_gmt":"2022-11-23T12:46:03","guid":{"rendered":"https:\/\/bundesstiftung-friedensforschung.de\/en\/2022\/11\/23\/datengestuetze-analyse-von-hate-speech\/"},"modified":"2025-10-30T17:29:39","modified_gmt":"2025-10-30T16:29:39","slug":"datengestuetze-analyse-von-hate-speech","status":"publish","type":"post","link":"https:\/\/bundesstiftung-friedensforschung.de\/en\/2022\/11\/23\/datengestuetze-analyse-von-hate-speech\/","title":{"rendered":"Datengest\u00fctze Analyse von Hate Speech"},"content":{"rendered":"\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-6uhx38-f5c8e80f0158cb9304b72e5ee8223b6d\">\n.flex_column.av-6uhx38-f5c8e80f0158cb9304b72e5ee8223b6d{\nbackground-color:#f2f2f2;\n}\n<\/style>\n<div  class='flex_column av-6uhx38-f5c8e80f0158cb9304b72e5ee8223b6d av_one_full  avia-builder-el-0  el_before_av_section  avia-builder-el-no-sibling  first flex_column_div  '     ><p>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-bfyke7-e27fc38c9bb972177c3c105b93572dff\">\n.av_font_icon.av-bfyke7-e27fc38c9bb972177c3c105b93572dff{\ncolor:#0a0a0a;\nborder-color:#0a0a0a;\n}\n.avia-svg-icon.av-bfyke7-e27fc38c9bb972177c3c105b93572dff svg:first-child{\nstroke:#0a0a0a;\nfill:#0a0a0a;\n}\n.av_font_icon.av-bfyke7-e27fc38c9bb972177c3c105b93572dff .av-icon-char{\nfont-size:40px;\n}\n<\/style>\n<span  class='av_font_icon av-bfyke7-e27fc38c9bb972177c3c105b93572dff avia_animate_when_visible av-icon-style- avia-icon-pos-left avia-svg-icon avia-font-svg_entypo-fontello avia-icon-animate'><a href='https:\/\/bundesstiftung-friedensforschung.de\/en\/thematische-foerderlinie-fb-3\/'   class='av-icon-char' data-av_svg_icon='left-open' data-av_iconset='svg_entypo-fontello' data-avia-icon-tooltip=\"&lt;br \/&gt;\nBack to overview&lt;br \/&gt;\n\"><svg version=\"1.1\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"11\" height=\"32\" viewBox=\"0 0 11 32\" preserveAspectRatio=\"xMidYMid meet\" aria-labelledby='av-svg-title-1' aria-describedby='av-svg-desc-1' role=\"graphics-symbol\" aria-hidden=\"false\">\n<title id='av-svg-title-1'>Left-open<\/title>\n<desc id='av-svg-desc-1'>Left-open<\/desc>\n<path d=\"M7.744 7.168q0.448-0.512 1.248-0.512t1.312 0.512q1.216 1.152 0 2.56l-5.952 6.272 5.952 6.208q1.216 1.408 0 2.56-0.512 0.512-1.28 0.512t-1.28-0.512l-7.232-7.552q-0.512-0.512-0.512-1.216 0-0.768 0.512-1.28 6.592-6.848 7.232-7.552z\"><\/path>\n<\/svg><\/a><\/span><br \/>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-5bx42c-d2071822166139d415c9b59a8623bbd2\">\n#top .hr.hr-invisible.av-5bx42c-d2071822166139d415c9b59a8623bbd2{\nheight:25px;\n}\n<\/style>\n<div  class='hr av-5bx42c-d2071822166139d415c9b59a8623bbd2 hr-invisible  avia-builder-el-2  el_after_av_font_icon  avia-builder-el-last '><span class='hr-inner '><span class=\"hr-inner-style\"><\/span><\/span><\/div><\/p><\/div>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-mepi6ss6-0e6d0ade76b049464284741c79780f99\">\n.avia-section.av-mepi6ss6-0e6d0ade76b049464284741c79780f99{\nmargin-top:-50px;\nmargin-bottom:25px;\n}\n<\/style>\n<div id='av_section_1'  class='avia-section av-mepi6ss6-0e6d0ade76b049464284741c79780f99 main_color avia-section-default avia-no-border-styling  avia-builder-el-3  el_after_av_one_full  el_before_av_hr  fade-up-section avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-1572'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-3o7c38-036c45f96348998cfdaa58fd6ac3354b sc-av_one_full av-equal-height-column-flextable'>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-3o7c38-036c45f96348998cfdaa58fd6ac3354b\">\n@-webkit-keyframes av_boxShadowEffect_av-3o7c38-036c45f96348998cfdaa58fd6ac3354b-column {\n0%   { box-shadow:  0 0 0 0 #e2e2e2; 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Euro<br \/>\n<strong>Duration:<\/strong> 30 months<\/p>\n<\/div><\/section><br \/>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-8i0p0f-2dba2e84b494cdd6604123278bf63f6c\">\n#top .hr.hr-invisible.av-8i0p0f-2dba2e84b494cdd6604123278bf63f6c{\nheight:5px;\n}\n<\/style>\n<div  class='hr av-8i0p0f-2dba2e84b494cdd6604123278bf63f6c hr-invisible  avia-builder-el-6  el_after_av_textblock  el_before_av_textblock '><span class='hr-inner '><span class=\"hr-inner-style\"><\/span><\/span><\/div><br \/>\n<section  class='av_textblock_section av-3jn0gf-67d18e5b784a47086d2f61754b4b5338 '   itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock av_inherit_color'  itemprop=\"text\" ><h2>Abstract<\/h2>\n<p>Social media have lately become one of the primary information channels for many individuals, which was exacerbated during the recent pandemic. In Germany, the percentage of individuals who use social media as a source for information has increased steadily from 2013 to 2020, reaching almost 40% in April 2020. As such, social media is a major example of the ambivalence of digitization: On the one hand, social media provide new opportunities for social interactions and political participation. On the other hand, it facilitates the dissemination of extremist thoughts and aggressive or harassing contents. In this context, the widely known term &#8220;hate speech&#8221; describes the aggressive and derogatory statements towards people who are assigned to certain groups.<\/p>\n<p>According to a representative survey run by Forsa in Germany in 2019, more than 70% of the respondents indicated to have already encountered online hate speech, and this share has likely risen since then. Encountering online hatred not only has negative consequences for the individuals themselves (e.g. emotional stress, fear and reputational damage), but also on the society as a whole: it has been shown that online hate speech translates into further\u00a0 negative real world outcomes such as societal segregation and xenophobic attacks.<\/p>\n<p>In order to reduce the dissemination of online hate speech, the German government implemented the Network Enforcement Act (NetzDG) in October 2017. This law obliges social platforms with more than 2 million users in Germany to delete posts and comments containing clearly hateful and insulting content within 24 hours after they have been reported.<\/p>\n<p>While Germany was the first country to implement a law for regulating user generated content (UGC), other countries and the European Commission also started to regulate UGC in the meantime, mostly with similar approaches. Yet, to the best of our knowledge, no empirical investigation has evaluated the effectiveness of such regulation. This project aims at closing this gap by answering the following Research Question: <em>Is the Network Enforcement Act effective in lowering the prevalence of hateful content on social networks in Germany?<\/em><\/p>\n<p>For addressing this research question, we will conduct empirical studies on one of the world&#8217;s largest social networks, i.e., Twitter. A data-based understanding of the prevalence of online hate speech and the impact of the NetzDG is crucial for establishing guidelines for developing future successful regulation of UGC in the EU and other countries. This claim is strengthened by the German government, which published an evaluation report of the NetzDG in September 2020, mentioning that due to the lack of data, an evaluation of the quality of the platforms\u2019 decisions to remove or keep content is not yet possible. Since the topic of online hate speech is also prevalent in the public discourse, we expect that the results of this project will encounter<br \/>\nhigh interest of policy makers, the scientific community, as well as the public media.<\/p>\n<p>In preliminary difference-in-difference analyses, we compared the prevalence of hateful content in migration-related tweets in the German and Austrian Twittersphere before and after the introduction of the law in Germany. By doing so, we isolate the causal effect of the law on a variety of measures related to hateful speech according to pre-trained algorithms and special dictionaries for the German language. Our preliminary results suggest a significant decrease in the amount of severely toxic tweets and tweets containing identity attacks. Furthermore, the sentiment of the tweets does not seem to be impacted by the NetzDG.<\/p>\n<p>In this project, we aim at validating the preliminary results described above by running different econometric specifications. Furthermore, we plan on extending the analysis by a sophisticated and all-encompassing measure of online hate speech. To that end, we want to develop a tool for automated hate speech classification, which could be adapted to other settings and languages for a broad application of the project outcomes. In addition, we plan to conduct a deeper analysis of mechanisms through which the law could potentially impact the spread of online hate in order to derive policy recommendations.<\/p>\n<p>Since the writing time of the research proposal, there have been a few recent developments that may slightly change the focus of the project. With the leverage of the military conflict in Ukraine, social media platforms faced a challenge to introduce governing rules for addressing the problem of hate speech in the context of an ongoing military conflict. Twitter responded to this challenge by introducing a new policy. Further, after Twitter was bought by Elon Musk, there have been radical changes in the company, which may also affect its handling of hate speech. Furthermore, when looking at topics which may involve hate speech, we will also look into recent emerging topics with a high potential for polarization, such as e.g. the above-mentioned war in Ukraine and climate activism.<\/p>\n<\/div><\/section><\/p><\/div><\/div><!--close column table wrapper. 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