SafeBear publishes the new edition of its monthly cyberbullying barometer targeting the main French political figures on the social network X. Conducted on posts published between 1 and 31 May 2026, this study analyses nearly 230,000 comments received by forty French political figures using SafeBear's proprietary technology for detecting and classifying toxic content. Key finding: 43% of the comments analysed are problematic, confirming the high level of verbal violence observed on the platform.
A structural toxicity in online debate
- 229,730 comments were analysed in May 2026, compared to 218,686 in April, representing a 5% increase.
- 98,030 comments were identified as problematic, representing a stable overall toxicity rate of 43%.
Political figures heavily exposed
- Jean-Luc Mélenchon remains the political figure receiving the highest number of toxic comments (16,118), ahead of Emmanuel Macron (7,763) and Gabriel Attal (7,564).
- Jordan Bardella ranks fourth with 7,255 problematic comments.
- The most active figures on X during May are Jean-Luc Mélenchon (145 posts), Marine Le Pen (129), Jordan Bardella (128), Éric Ciotti (123), Nicolas Dupont-Aignan (115), Florian Philippot (112) and François Ruffin (103).
Variable intensity depending on profile
- As a proportion of comments received, Nicolas Sarkozy records the highest toxicity rate (64%), ahead of François Hollande (57%) and Jean-Luc Mélenchon (54%).
- The largest increases in toxic comments compared to April concern Florian Philippot (+174%), Marine Le Pen (+82%), Jean-Luc Mélenchon (+76%) and Gabriel Attal (+58%).
- Conversely, Aurore Bergé records the largest drop in problematic comment volume (-65%).
Well-identified forms of violence
Insults represent the most frequent form of violence observed on X. Of the 98,030 problematic comments detected in May, SafeBear recorded 60,528 insults, 23,302 denigration messages, 17,599 pieces of identity-based hate content and 4,686 messages containing threats.
"When nearly one in two comments addressed to a public figure contains a form of verbal aggression, we are no longer dealing with marginal behaviour but with a structural phenomenon that affects the quality of democratic debate," says Lyess MEDDAHI, Strategy Director at SafeBear.
| CYBERBULLYING OBSERVATORY ON THE SOCIAL NETWORK X | |||||||
|---|---|---|---|---|---|---|---|
| PUBLIC FIGURES | TWEETS POSTED |
COMMENTS RECEIVED | PROBLEMATIC COMMENTS |
TOXICITY RATE* | |||
| MAY 26 | MAY 26 | APR. 26 | MAY 26 | APR. 26 | MAY 26 | APR. 26 | |
| Jean-Luc Mélenchon | 145 | 30 084 | 16 166 | 16 118 | 9 165 | 54% | 57% |
| Emmanuel Macron | 77 | 21 099 | 24 649 | 7 763 | 9 955 | 37% | 40% |
| Gabriel Attal | 90 | 17 270 | 10 461 | 7 564 | 4 791 | 44% | 46% |
| Jordan Bardella | 128 | 17 212 | 17 016 | 7 255 | 7 411 | 42% | 44% |
| Marine Le Pen | 129 | 15 874 | 9 278 | 6 331 | 3 483 | 40% | 38% |
| Florian Philippot | 112 | 11 987 | 4 315 | 5 198 | 1 894 | 43% | 44% |
| Olivier Faure | 61 | 11 394 | 13 766 | 4 924 | 6 235 | 43% | 45% |
| Bruno Retailleau | 71 | 11 030 | 10 346 | 4 937 | 4 330 | 45% | 42% |
| Sarah Knafo | 61 | 10 171 | 10 045 | 3 450 | 2 889 | 34% | 29% |
| David Lisnard | 84 | 7 851 | 6 699 | 1 935 | 2 084 | 25% | 31% |
| Eric Zemmour | 53 | 7 702 | 6 404 | 3 351 | 2 984 | 44% | 47% |
| Yaël Braun-Pivet | 37 | 6 535 | 6 726 | 2 981 | 3 175 | 46% | 47% |
| François Ruffin | 103 | 6 209 | 5 253 | 2 497 | 2 044 | 40% | 39% |
| N. Dupont-Aignan | 115 | 5 604 | 7 164 | 2 361 | 3 035 | 42% | 42% |
| Marion Maréchal | 55 | 5 473 | 5 655 | 2 632 | 2 673 | 48% | 47% |
| Clémentine Autain | 67 | 4 220 | 4 379 | 1 828 | 1 978 | 43% | 45% |
| Ségolène Royal | 36 | 3 857 | 4 781 | 2 012 | 2 436 | 52% | 51% |
| Eric Ciotti | 123 | 3 575 | 4 724 | 1 286 | 1 305 | 36% | 28% |
| Gérald Darmanin | 69 | 3 269 | 2 996 | 1 238 | 1 062 | 38% | 35% |
| Dominique de Villepin | 33 | 3 214 | 3 862 | 1 352 | 1 925 | 42% | 50% |
| Nathalie Arthaud | 65 | 2 874 | 4 784 | 1 160 | 2 520 | 40% | 53% |
| Élisabeth Borne | 31 | 2 740 | 450 | 1 076 | 167 | 39% | 37% |
| Fabien Roussel | 75 | 2 725 | 4 101 | 1 024 | 1 822 | 38% | 44% |
| Laurent Wauquiez | 20 | 2 212 | 2 720 | 899 | 1 177 | 41% | 43% |
| Aurore Bergé | 36 | 2 057 | 5 067 | 933 | 2 693 | 45% | 53% |
| Jérôme Guedj | 31 | 1 812 | 2 826 | 821 | 1 395 | 45% | 49% |
| Thierry Breton | 13 | 1 672 | 659 | 858 | 284 | 51% | 43% |
| Valérie Pécresse | 21 | 1 559 | 1 699 | 588 | 630 | 38% | 37% |
| Edouard Philippe | 5 | 1 528 | 459 | 744 | 236 | 49% | 51% |
| Raphaël Glucksmann | 7 | 1 426 | 1 047 | 591 | 500 | 41% | 48% |
| Xavier Bertrand | 26 | 1 357 | 1 377 | 677 | 660 | 50% | 48% |
| Bernard Cazeneuve | 13 | 965 | 508 | 373 | 182 | 39% | 36% |
| Carole Delga | 26 | 856 | 1 487 | 304 | 578 | 36% | 39% |
| François Asselineau | 17 | 607 | 8 158 | 202 | 3 296 | 33% | 40% |
| Rachida Dati | 13 | 566 | 186 | 233 | 72 | 41% | 39% |
| Marine Tondelier | 78 | 444 | 4 135 | 202 | 1 988 | 45% | 48% |
| Michel Barnier | 17 | 188 | 1 992 | 67 | 747 | 36% | 38% |
| François Hollande | 6 | 153 | 1 524 | 87 | 738 | 57% | 48% |
| Nicolas Sarkozy | 1 | 146 | — | 94 | — | 64% | — |
| Boris Vallaud | 43 | 113 | 130 | 42 | 46 | 37% | 35% |
| Gérard Larcher | 8 | 100 | 692 | 42 | 301 | 42% | 43% |
| TOTAL | 2 201 | 229 730 | 218 686 | 98 030 | 94 886 | 43% | 43% |
Source: SafeBear, May 2026
*Toxicity rate: ratio between the number of comments received and the number of problematic comments
|
CYBERBULLYING OBSERVATORY ON THE SOCIAL NETWORK X
Categories of toxic messages – May 2026
|
||||||
|---|---|---|---|---|---|---|
| TOTAL | OF WHICH | |||||
| PUBLIC FIGURES | Problematic comments |
Disparagement | Obscene | Insults | Identity-based hate |
Threats |
| Jean-Luc Mélenchon | 16 118 | 3 730 | 59 | 10 207 | 3 762 | 782 |
| Emmanuel Macron | 7 763 | 1 702 | 61 | 4 398 | 1 703 | 461 |
| Gabriel Attal | 7 564 | 1 782 | 49 | 5 337 | 744 | 230 |
| Jordan Bardella | 7 255 | 1 816 | 25 | 4 726 | 1 005 | 311 |
| Marine Le Pen | 6 331 | 1 941 | 21 | 3 550 | 1 130 | 344 |
| Florian Philippot | 5 198 | 1 177 | 37 | 3 004 | 454 | 376 |
| Olivier Faure | 4 924 | 1 115 | 17 | 3 482 | 676 | 141 |
| Bruno Retailleau | 4 937 | 1 192 | 14 | 2 980 | 909 | 232 |
| Sarah Knafo | 3 450 | 750 | 31 | 1 832 | 937 | 204 |
| David Lisnard | 1 935 | 407 | 3 | 1 102 | 354 | 128 |
| Eric Zemmour | 3 351 | 645 | 9 | 1 712 | 1 251 | 143 |
| Yaël Braun-Pivet | 2 981 | 845 | 19 | 1 627 | 477 | 134 |
| François Ruffin | 2 497 | 546 | 8 | 1 718 | 332 | 100 |
| N. Dupont-Aignan | 2 361 | 474 | 15 | 1 515 | 208 | 139 |
| Marion Maréchal | 2 632 | 671 | 19 | 1 317 | 875 | 100 |
| Clémentine Autain | 1 828 | 361 | 14 | 1 256 | 304 | 80 |
| Ségolène Royal | 2 012 | 499 | 18 | 1 275 | 383 | 54 |
| Eric Ciotti | 1 286 | 297 | 5 | 762 | 216 | 94 |
| Gérald Darmanin | 1 238 | 356 | 22 | 612 | 262 | 95 |
| Dominique de Villepin | 1 352 | 353 | 6 | 818 | 198 | 53 |
| Nathalie Arthaud | 1 160 | 204 | 3 | 811 | 146 | 65 |
| Élisabeth Borne | 1 076 | 259 | 5 | 739 | 111 | 37 |
| Fabien Roussel | 1 024 | 212 | 6 | 667 | 133 | 39 |
| Laurent Wauquiez | 899 | 225 | 3 | 669 | 48 | 38 |
| Aurore Bergé | 933 | 262 | 12 | 474 | 230 | 38 |
| Jérôme Guedj | 821 | 171 | 3 | 565 | 170 | 30 |
| Thierry Breton | 858 | 228 | 1 | 613 | 63 | 34 |
| Valérie Pécresse | 588 | 146 | 4 | 384 | 88 | 24 |
| Edouard Philippe | 744 | 180 | 1 | 477 | 75 | 55 |
| Raphaël Glucksmann | 591 | 145 | 1 | 401 | 54 | 18 |
| Xavier Bertrand | 677 | 147 | 2 | 485 | 104 | 20 |
| Bernard Cazeneuve | 373 | 105 | 2 | 251 | 32 | 20 |
| Carole Delga | 304 | 84 | 1 | 198 | 40 | 18 |
| François Asselineau | 202 | 56 | 2 | 90 | 32 | 7 |
| Rachida Dati | 233 | 71 | 1 | 119 | 46 | 13 |
| Marine Tondelier | 202 | 51 | 0 | 145 | 21 | 5 |
| Michel Barnier | 67 | 14 | 1 | 46 | 8 | 0 |
| François Hollande | 87 | 20 | 0 | 61 | 2 | 11 |
| Nicolas Sarkozy | 94 | 30 | 1 | 56 | 4 | 11 |
| Boris Vallaud | 42 | 13 | 0 | 23 | 7 | 1 |
| Gérard Larcher | 42 | 20 | 0 | 24 | 5 | 1 |
| TOTAL | 98 030 | 23 302 | 501 | 60 528 | 17 599 | 4 686 |
Source: SafeBear, May 2026
A comment may fall into multiple categories.
Definition of indicators Problematic messages are classified into 5 categories:
- Disparagement: personal attacks & defamation. Rude or disrespectful messages intended to belittle, offend or embarrass, and to discredit;
- Obscene: sexual cyberviolence. Messages with offensive language, sexual content or explicit material unsuitable for the general public;
- Identity-based hate: racist, antisemitic, Islamophobic, sexist, homophobic, xenophobic hatred. Messages that encourage hatred or discrimination based on identity (race, religion, gender, etc.);
- Insults: messages containing insults or disparaging remarks targeting individuals or groups;
- Threats: messages containing threats of violence or harm towards individuals or groups.
