Down Ranking Polarizing Content Lowers Emotional Temperature On Social

Bonisiwe Shabane
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down ranking polarizing content lowers emotional temperature on social

Reducing the visibility of polarizing content in social media feeds can measurably lower partisan animosity. To come up with this finding, my colleagues and I developed a method that let us alter the ranking of people’s feeds, previously something only the social media companies could do. Reranking social media feeds to reduce exposure to posts expressing anti-democratic attitudes and partisan animosity affected people’s emotions and their views of people with opposing political views. I’m a computer scientist who studies social computing, artificial intelligence and the web. Because only social media platforms can modify their algorithms, we developed and released an open-source web tool that allowed us to rerank the feeds of consenting participants on X, formerly Twitter, in real time. Drawing on social science theory, we used a large language model to identify posts likely to polarize people, such as those advocating political violence or calling for the imprisonment of members of the opposing...

These posts were not removed; they were simply ranked lower, requiring users to scroll further to see them. This reduced the number of those posts users saw. We ran this experiment for 10 days in the weeks before the 2024 U.S. presidential election. We found that reducing exposure to polarizing content measurably improved participants’ feelings toward people from the opposing party and reduced their negative emotions while scrolling their feed. Importantly, these effects were similar across political affiliations, suggesting that the intervention benefits users regardless of their political party.

A new Stanford-led study is challenging the idea that political toxicity is simply an unavoidable element of online culture. Instead, the research suggests that the political toxicity many users encounter on social media is a design choice that can be reversed. Researchers have unveiled a browser-based tool that can cool the political temperature of an X feed by quietly downranking hostile or antidemocratic posts. Remarkably, this can occur without requiring any deletions, bans, or cooperation from X itself. The study offers the takeaway that algorithmic interventions can meaningfully reduce partisan animosity while still preserving political speech. It also advances a growing movement advocating user control over platform ranking systems and the algorithms that shape what they see, which were traditionally guarded as proprietary, opaque, and mainly optimized for engagement rather...

The research tool was built by a multidisciplinary team across Stanford, Northeastern University, and the University of Washington, composed of computer scientists, psychologists, communication scholars, and information scientists. Their goal in the experiment was to counter the engagement-driven amplification of divisive content that tends to reward outrage, conflict, and emotionally charged posts, without silencing political speech. Using a large language model, the tool analyzes posts in real time and identifies several categories of harmful political subject matter, including calls for political violence, attacks on democratic norms, and extreme hostility toward... When the system flags such content, it simply pushes those posts lower in the feed so they are less noticeable, like seating your argumentative uncle at the far end of the table during the... ���u4�|��"� ���|!����;d?i[)d�D-u�|,� /���.��T� d �V��Cw��}����D�㳀{��'���^�mx>'I$� "#hg:�n�f�[��8���^���f����q�9��*%rJ6���!x^&F�D���8�����!z����_]��� n���9��XIO2���Ԓyd)���#�ɻ�ZD��dz���s/�}����w K��T�D*"#�E~���%0�a!��؀#�G�#|N�i"=1�#Nn�g>���?�˨�,a��Q�,<'�"�W�w���o��ui�,�e�5��H��9�pq�� W���I8�k���Qb@�%�.��53�L"����"��<������9�}6R���n4��������x[M[�q�+������q]��\%W��ss�5\�{���;�]�~�G�u��O�}���Ϗ�g������Q�[—*��f�UX��j�����+�+�;��4Uh�`;��G����+��=4�O�+�;hϣa7�����d�����Uoڛ��y��5��^������ �I�{�6U<�,F�h�������� d>=�2@3Q~7J^�2y?���N5�(|�눝�ҧ��h/�}� �p� �tr;l���K�h�7�g�/��,�3'�1���<�}?7�~������d?�l2���pUtnQuQ�țt"�H�H P��VҁpB<,"��z�9�̄#�>����/p���PR�+�vX��0W���'�## �g����x� Ы�B��W�n�E�@�q��\�v1=�z|֢��т&����;Т*�a� �z���P)?�� p����?X*��7×�6�ő�`^%?µ}�Џ��]i#���k��_�vq�w����>�h�?�aP(������ =�:��38ʳ��n?dGn�Mr?n��$ ����D��{�I��j?�q���� j�P����LD=�D-P[3��,��#�H<�@ӱ�=�+��p��J]�~T��2�^���E�8[>��(E?n�d�s��V%�J�����dvs4;��DG�͜���o�K7�Ug�z.)1�#�GZ'����ntcs�޹��?�λ���R��U�� �f�R�>���s�H�_�X�z�U����m�b�XP�$"O,��|FK��ov�t� %ٝ]~7dK�ݤ������ v��&rq交t›�!�c77dzL��& ����!^��{4ig�ʸ��Y �x�7�GRU�����9>�d�e�7�iܾs��&�_ٷ�K]����� b�R,��2K�#���|���o�F^��������Z�����g�Ǭ�ur������5/2�V�<�pM@�ь7 �Z#�a�� 6�4,ꍦ��9���-��P��v�) Q��3I%�QKN^��l��H���8r�¹����#C�����쉶K���y1�HW�_0t��D�Չ�Z��F�`���La�|�(�����b6+̙�Qa��u::�lr���yk��L����8/Xr:���N�'�Dڶ''����.�;r���r�|�wךƑ�_j;q6�ψ{���R HV$3^���t�~��M��U��4�z�u����q�l��&OVO֏��b��X�<��V���j^�Z�^#��8A����?6']�n�6���dj hE-ծr[�����@a�����ӈ3X9���&���8��I� ƉV�l�8��r:��D�n,�ϛ�V �|tӬ�����>zl��7�g�ϻ��%<�����"�H$r`�ڝ�ȃ���h�ىK�G'q/���`k@�FK�d~]I�i��y��@9�@... ���G���~Ч@�T�aH�� B#���� f��`A���������6��#t"�\�@�'BŸ� n,���e?�8�?� R?B��0d!�@a6�F�9A� �c��<�"̇�] ����8��A!�#��a7(@Xq�ݡ+���b膰��B��Y��a/聰 J����?���>�a_+�� � a?荰�S�"7�A��""� � VA?���2u�@�P��B��"��@��a�08� ��p A8�"���������a�V�#N��b�p�J��a4��[���)0a �Gx)�SaB�oP N��NG�̀j�3a2�Yp ��0%�%��p.� ������P��.�i�t�� f \�������,��`�:����g��!\ �^��SX ��E���^��X�p-,Ax,M��u�C����հ"� \+^���<�1\�n��7���+S�fX��X�5[~7�Uo�u��z������j���5צN��9�6 � 6"�6��;��;�z�w��ԇp7܀�؂�^n��w�6��#���>� |~��a�}�}xnM���m��>��p�'�N�O��wr�4܃p܋��C�� h�����M�@�]� �� �8|B� #�� <���ƒ�x�x�@���[�)��������Ro�ah@�"�N�/q�24"��I� �@�#�᫰�k� £Ќ�ϰ�1�����_��Ro�_�7�߂C߆��_�� �#|^@x#|����E��K?��S��$�����1��...

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A new tool shows it is possible to turn down the partisan rancor in an X feed — without removing political posts and without the direct cooperation of the platform. The study, from researchers at the University of Washington, Stanford University and Northeastern University, also indicates that it may one day be possible to let users take control of their social media algorithms. The researchers created a seamless, web-based tool that reorders content to move posts lower in a user’s feed when they contain antidemocratic attitudes and partisan animosity, such as advocating for violence or jailing supporters... Researchers published their findings Nov. 27 in Science. Assistant Professor of Computer Science, Johns Hopkins University

This research was partially supported by a Hoffman-Yee grant from the Stanford Institute for Human-Centered Artificial Intelligence. Reducing the visibility of polarizing content in social media feeds can measurably lower partisan animosity. To come up with this finding, my colleagues and I developed a method that let us alter the ranking of people’s feeds, previously something only the social media companies could do. Reranking social media feeds to reduce exposure to posts expressing anti-democratic attitudes and partisan animosity affected people’s emotions and their views of people with opposing political views. I’m a computer scientist who studies social computing, artificial intelligence and the web. Because only social media platforms can modify their algorithms, we developed and released an open-source web tool that allowed us to rerank the feeds of consenting participants on X, formerly Twitter, in real time.

Organize your preprints, BibTeX, and PDFs with Paperpile. Enhance arXiv with our new Chrome Extension. Abstract: There is widespread concern about the negative impacts of social media feed ranking algorithms on political polarization. Leveraging advancements in LLMs, we develop an approach to re-rank feeds in real-time to test the effects of content that is likely to polarize: expressions of antidemocratic attitudes and partisan animosity (AAPA). In a preregistered 10-day field experiment on X/Twitter with 1,256 consented participants, we increase or decrease participants' exposure to AAPA in their algorithmically curated feeds. We observe more positive outparty feelings when AAPA exposure is decreased and more negative outparty feelings when AAPA exposure is increased.

Exposure to AAPA content also results in an immediate increase in negative emotions, such as sadness and anger. The interventions do not significantly impact traditional engagement metrics such as re-post and favorite rates. These findings highlight a potential pathway for developing feed algorithms that mitigate affective polarization by addressing content that undermines the shared values required for a healthy democracy. Organize your preprints, BibTeX, and PDFs with Paperpile. In the ongoing discourse on the influence of social media on political polarization, the paper authored by Piccardi et al. is a timely exploration of how algorithmic curation of social media feeds can affect user sentiment and polarization.

The paper specifically investigates the effects of exposure to content reflecting antidemocratic attitudes and partisan animosity (AAPA) in social media feeds, focusing on whether intervention in real-time content ranking can influence affective polarization. Communications Psychology volume 3, Article number: 11 (2025) Cite this article The generation and distribution of hyper-partisan content on social media has gained millions of exposure across platforms, often allowing malevolent actors to influence and disrupt democracies. The spread of this content is facilitated by real users’ engaging with it on platforms. The current study tests the efficacy of an ‘inoculation’ intervention via six online survey-based experiments in the UK and US. Experiments 1–3 (total N = 3276) found that the inoculation significantly reduced self-reported engagement with polarising stimuli.

However, Experiments 4–6 (total N = 1878) found no effects on participants’ self-produced written text discussing the topic. The implications of these findings are discussed in the context of the literature on polarisation and previous interventions to reduce engagement with disinformation. In the last few decades, political polarisation has grown in numerous countries worldwide1,2,3. Of particular concern is the rise in affective polarisation, that is the disparity between feelings of warmth towards political in-groups versus political out-groups4. This concept of affective polarisation is rooted in Social Identity Theory5, which posits that humans are naturally inclined to categorise themselves and others into in-groups and out-groups, with greater salience of these identities encouraging... However, rather than observing any great increase in in-group warmth, instead researchers have noted declining warmth towards political foes, or a growth in so called negative partisanship6.

The rise in affective polarisation may in part be driven by our increased dependence upon social media for news gathering and the explosion in the number of hyper-partisan outlets (e.g. Breitbart) that create and spread hyper-partisan content on social media7,8,9,10. Much of this content could be classed as disinformation, the deliberate creation and distribution of false or manipulated information7,8,11. Creators of such content have varied objectives, including monetisation of the sharing of sensationalist or partisan news, but often there is an incentive to influence and reduce trust in democratic processes by increasing group... Indeed, exposure to partisan reporting that is critical of those out-groups has been found to decrease ratings of trust and liking of those groups, feeding into negative partisanship6,16. The full scale of the problem has become clearer over the last decade.

For example, investigations into the reach of foreign disinformation operations, including the internet research agency based in St Petersburg, have found hundreds of millions of exposures to disinforming and hyper-partisan posts on Twitter and...

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