{"id":16955,"date":"2025-06-09T17:39:12","date_gmt":"2025-06-09T15:39:12","guid":{"rendered":"https:\/\/zawia3.com\/?p=16955"},"modified":"2026-10-23T21:15:05","modified_gmt":"2026-10-23T19:15:05","slug":"egyptian-pilgrims","status":"publish","type":"post","link":"https:\/\/zawia3.com\/en\/egyptian-pilgrims\/","title":{"rendered":"Digital Bullying and Hate Speech: Who Amplified Attacks on Egyptian Pilgrims?"},"content":{"rendered":"

Social media platforms witnessed an incitement campaign against Egyptian Hajj and Umrah pilgrims, which began tentatively in January of this year and peaked last March, coinciding with the Ramadan Umrah, before its intensity declined markedly over the past months of April and May. In this investigation, conducted by Zawia3 with the support of the Arab Fact-Checkers Hub (AFH) (as part of the digital tools support programme), we examine whether the incitement campaigns against Egyptian Umrah pilgrims on digital platforms are systematic or spontaneous. Who are the parties or entities active in steering them? Are these campaigns linked to the repercussions of the last Hajj season, which saw deaths among Egyptian pilgrims? We also seek to reveal whether the campaigns are systematic or spontaneous, based on patterns of posting, timing and coordination, and try to understand the organisational structure of the incitement campaigns.<\/span><\/p>\n

The social media platform “X” had seen hashtags related to Hajj and Umrah circulated intensively over the past four months, the most prominent of which were: #Hajj_disaster, #Hajj_1446AH, #Hajj_is_not_safe, #Pilgrims_thank_Saudi_Arabia #Hajj_is_safe_by_God_then_by_the_Saudi_state, #No_Hajj_without_a_permit, #The_Meccan_Haram, #The_Sacred_House_of_God, #Saudi_Arabia, #Hajj_season, #The_Noble_Meccan_Haram, #Hajj_is_a_red_line, #We_are_the_servants_of_the_Haram, #The_road_to_the_rites, #Good_tidings_of_hospitality, #The_guides, #Hajj_2025, #Tourism_companies, #Chamber_of_tourism_companies, #Holy_Mecca, #Mecca_rains, #Success_of_the_Hajj_season_1445, #Their_negligence_killed_the_pilgrims .<\/span><\/p>\n

At the same time, incitement discourse against Egyptian Hajj and Umrah pilgrims rose, and users on “X” circulated tweets carrying hashtags such as: #Egypt, #Al_Masarya, #The_Egyptian, #The_Egyptian_woman, #The_Egyptians, #Enough #Egyptian, #Kabsa_and_taameya_together_never, #The_human_invasion, #Free, #Deporting_the_Egyptians_is_the_Saudis_demand, alongside offensive hashtags such as: #The_repeated_barking, #Expel_Al_Saud_from_the_Arabian_Peninsula, #By_their_incitement_they_destroyed_them, #Internationalise_the_Two_Holy_Mosques .<\/span><\/p>\n

The campaign came about 6 months after the wave of deaths<\/a> that occurred during the 2024 Hajj season in the period from 14 to 19 June 2024, when about 1,426 pilgrims of various nationalities died while performing the Hajj in Mecca because of extreme heat exceeding 50 degrees Celsius, 85% of whom were pilgrims on visit visas, according to earlier media statements<\/a> by the Saudi minister of health, while the number<\/a> of Egyptian pilgrims who died while performing the rites last year reached about 672 people.<\/p><\/blockquote>\n

First, we searched for keywords such as: Egyptian Umrah pilgrims, the Egyptian Umrah pilgrims, Egypt and Hajj, deaths of Egyptian pilgrims, Hajj problems in Egypt, negligence in Hajj, the Hajj crisis, Egyptian Umrah, and we found more than 200 different hashtags on X (formerly Twitter), as the platform most used in political campaigns and coordinated incitement. The most circulated hashtags in the period from 1 January 2025 to 30 May 2025 were: #The_competent_authorities, #The_human_invasion, #Free, #Al_Masar, all of them combined hashtags, most of them offensive, circulated 235 times; the hashtags #The_Eid_is_two_Eids and #The_citizen_is_the_leaderships_priority, which were circulated 168 times; then the hashtags #Hajj_1446AH, #Hajj_is_not_safe, #Hajj_disaster, #No_Hajj, hashtags that question the safety of Hajj and promote crises, circulated 137 times.<\/span><\/p>\n

Meanwhile, the hashtag #We_are_the_servants_of_the_Haram was circulated about 97 times, the two hashtags #Sisi_a_leader_the_size_of_a_world and #Egyptians_planet_of_joy 55 times, and the hashtags #Hajj, #The_agreed_plan, #The_Egyptians, #Egyptian about 52 times, in addition to awareness and organisational hashtags such as #Enriching_the_guests, about 35 times. The two hashtags #The_Egyptian_army_is_capable_and_ready and #The_Egyptian_people_have_their_armys_back were circulated<\/span> 34 times, the hashtag #Egypt 24 times, the two hashtags #Egyptian_women and #The_Egyptians 18 times, the hashtag #Saudi 17 times, #Great_Saudi_Arabia 22 times, and the two hashtags #Hajj_not_safe and #Hajj_is_not_safe 10 times. The hashtag #Deporting_the_Egyptians_is_the_Saudis_demand, which contains a direct call against Egyptian Umrah pilgrims, was circulated 8 times, alongside hashtags such as #Al_Masarya, #The_Egyptian, #Al_Masriben, which contained repeated spelling mistakes of the same word\/meaning and were circulated only 7 times.<\/span><\/p>\n

\"The
The most circulated words and entities related to the topic or the campaign<\/figcaption><\/figure>\n

The infographic shows keywords (in dark blue) such as: “distribution”, “exploitation”, “the beggar”, “begging”; hashtags (in light blue) such as: #Egyptian, #The_Egyptian_woman, #The_Egyptian, #The_Egyptians, #The_human_invasion; people (in purple): “Aref”, “chaotic”, “hungry beggar”; and locations appear (in orange): “Mecca”, “Medina”, “Saudi Arabia”, “Holy Mecca”, “Egypt”. Brown indicates emojis: “SA”, laughing faces, broken hearts, “X” signs, etc.<\/span><\/p>\n

The keywords reflect a geographical and religious focus, through the clear repetition of the words “Mecca” and “Medina”, linked to Hajj\/Umrah, such as “visitors to the Two Holy Mosques”, “Holy Mecca” and “touristic for Umrah”, with a clearly negative character linked to Egyptian nationality, which appears in the abundance of hashtags linked to “Egyptian” and “Egyptians”, such as #The_Egyptian, #The_Egyptian_woman, #The_Egyptians, and the circulation of negatively connoted words such as “exploitation”, “beggar”, “begging”, “hasiro”, “human_invasion”, along with words suggesting accusations or popular resentment, such as “belonging to one”, “allocated for distribution”, “chaotic”, “hungry beggar”, “non-Egyptian”, and the use of negative emojis (\u274c\ud83d\udc94\ud83d\ude12). The likely context of the tweets is linked to the behaviour of some Egyptian visitors in Mecca, the distribution of meals, and allegations of begging or religious\/social exploitation.<\/span><\/p>\n

 <\/p>\n

Recommended reading: <\/b>Zawia3 Merchants of the rites: how did fake visas cause the deaths of Egyptian pilgrims?<\/b><\/a><\/h3>\n

\"\"
\nClear dominance of negative discourse<\/b><\/h1>\n

An analysis of data on 5,179 tweets on “X” in the period from 1 January 2025 to 30 May 2025, using the Meltwater tool (a comprehensive platform for “media monitoring”, “social media” and “consumer intelligence”), shows that 3,133 tweets were negative in character, 1,810 tweets neutral and 234 tweets positive.<\/span><\/p>\n

March 2025 saw an abnormal explosion in negative discourse (2,458 negative posts out of 3,133, i.e. 78% of all negative discourse), compared with January, which recorded 22 negative posts, February: 31 posts, April: 452 posts and May: 170 posts. The sudden escalation in March 2025 suggests a coordinated campaign that began suddenly and intensively and then gradually faded over the following two months, which is a typical feature of paid or coordinated campaigns (botnet campaigns or mobilisation campaigns, Manual Coordinated Campaign).<\/span><\/p>\n

\"A
A chart showing the share of sentiment in the tweets, whether positive, negative or neutral<\/figcaption><\/figure>\n

 <\/p>\n

The clear dominance of negative discourse is evident, as the total number of negative posts reaches 3,133, a share of 60. 5 %, against only 234 positive posts, a share of 4.5%, and 1,811 neutral posts, a share of 35%. This sharp gap suggests a state of mobilisation or non-spontaneous steering in public discourse, especially when looking at the context and the topics, in addition to a disproportionate geographical concentration: although the negative discourse came from 48 countries, the most prominent shares came from specific countries, which indicates coordinated activity.<\/span><\/p>\n

Saudi Arabia topped the countries with the most negative tweets in this context by a huge margin, recording 743 negative tweets out of 1,150 tweets, followed by Egypt with about 229 tweets out of 351, then distant and non-Arab countries such as America and Britain, which indicates the international spread of the discourse or interference from outside the regional context: the United States of America came third, recording 57 negative tweets out of 90, Britain was in fourth place with 25 negative tweets out of 35, then Kuwait with 14 negative tweets out of 22. The rest of the negative tweets were distributed among other countries such as: (the UAE, Bahrain, Iraq, Palestine, Russia, Qatar, Spain, Ghana, Sweden, Mauritania, Germany, France, Turkey, Jordan, the occupied Palestinian territories, Malaysia, Lebanon, Sudan, Libya, Syria, Morocco, Oman).<\/span><\/p>\n

\"A
A chart showing the locations of the accounts that tweeted most about the topic<\/figcaption><\/figure>\n

Using the Python language (a general-purpose programming language used in diverse fields such as web development, data science, machine learning, task automation and writing programs), we found that the most frequent words in the negative tweets were: “Umrah pilgrims”, which was mentioned (3,252 times), then “Egyptians”, which recurred (2,758 times), followed by words such as “the Haram”, “tourism”, “Umrah”, “Mecca” and “food”. Words such as “whether” and “what” also appear frequently, indicating questioning or scepticism. We detected indicators of systematic incitement discourse, most notably the high frequency of words such as “Egyptian Umrah pilgrims”, “food” and “tourism”.<\/span><\/p>\n

By analysing the volumes and the temporal burst, we found that total negative tweets reached 3,133 out of 5,179 tweets (more than 60%), a high proportion, and that they saw a sudden peak in March 2025, as 2,458 negative tweets appeared in March alone, representing 78.5% of all negative tweets, while in January and February the total was only 53 tweets, indicating a concentrated and sudden media campaign, coordinated in time and most likely linked to a specific event. We also noticed a large number of retweets (Retweet) of the negative tweets, numbering (1,825) and making up 61% of those tweets, which may indicate directed reposting.<\/span><\/p><\/blockquote>\n

The analysis of the temporal trend of negative sentiment showed that the number of negative tweets reached 22 in January 2025 and 31 in February, but jumped to 2,458 tweets in March, fell to 452 in April and reached 170 negative tweets in May, which has just ended. The most prominent accounts in terms of negative activity were: @_900_900, which posted 22 negative tweets; @111104427l1ahnl, which tweeted 17 negative tweets; followed by @cookingarba1 with 12 tweets; then @abdullah1383_ with about 11 tweets; followed by the account @hamdamhamd3, tweeting 10 negative tweets. We conclude from this that a specific group of accounts was responsible for the largest part of the negative content, some of which posted no positive content at all, and that most of these accounts are very active in expressing negative opinion, indicating the possibility of mobilisation or coordination in posting: excessively “active” accounts that may be angry individuals or “directed” (bot or semi-bot).<\/span><\/p>\n

\"Number
Number of negative tweets by month<\/figcaption><\/figure>\n

 <\/p>\n

Recommended reading: <\/b>A decision describes Egyptian women as \u00ablower categories\u00bb and requires a permit to travel to Saudi Arabia<\/b><\/a><\/p>\n

\"\"<\/p>\n

More mentions and less reach<\/b> <\/span><\/h1>\n

By analysing mention trends (Mentions Trend), we found that the total number of mentions in the period from 1 January 2025 to 26 May last reached 5,180, an increase of 553% over the previous period (793), and that the daily average was 34, an increase of 553% over the previous period (5). There was a sharp rise in the number of mentions in the period between mid- and late March, with a peak of nearly 800\u2013900 mentions a day, and another rise appeared in the period from 21 to 26 May 2025, while the remaining periods (from the beginning of January to early March, and from mid-April to mid-May) were almost stable.<\/span><\/p>\n

It is possible that an event, such as (the Ramadan Umrah), or a promotional campaign led to this large rise in late March, while the rise at the end of May may be the result of a follow-up campaign, a new announcement or a controversy, most likely coinciding with the start of the Hajj rites.<\/span><\/p>\n

\"A
A chart showing the analysis of mention trends (Mentions Trend)<\/figcaption><\/figure>\n

 <\/p>\n

Meanwhile, the analysis of the reach trend (Reach Trend) indicates that total reach in the period from 1 January 2025 to 26 May last reached 60 million, a decrease of 17% from the previous period (72.5 million), and that the average daily reach was 403,000, a decrease of 17% from the previous period (487,000).<\/span><\/p>\n

Reach recorded rises coinciding with the period from 22 March to 6 April, with scattered peaks appearing between 28 April and 1 May, and another large one in the period from 6 May to 11 May, followed by a decline and then a limited rise in the period from 21 to 26 May. Overall, reach was more volatile than the number of mentions, and despite the increase in the number of mentions, the reach rate fell, indicating that most mentions came from small accounts or a limited audience; the campaign may have spread virally within a specific group rather than widely, and the influence of major accounts or influencers was stronger in the previous period.<\/span><\/p>\n

 <\/p>\n

\"A
A chart showing the analysis of the reach trend (Reach Trend)<\/figcaption><\/figure>\n

 <\/p>\n

Recommended reading: <\/b>How did \u201celectronic committees\u201d exploit Gaza and the anniversary of 25 January in an organised propaganda campaign?<\/b><\/a><\/p>\n

\"\"
\nSystematic incitement through the stereotyped repetition of phrases and sentences<\/b><\/h1>\n

The initial analysis of the discourse in the negative tweets, based on the most frequent words, showed that the general features of the discourse were critical\/denunciatory, pointing to an interrogative or offensive character, and that it was centred on Egyptian nationality, as the words “Egyptians”, “Egyptian Umrah pilgrims”, “Egypt” and “Egyptian” appeared frequently, indicating a discourse that focuses on a specific identity and places it at the centre of accusation or suffering, with a state of emotional charging through words such as “food”, “the Haram” and “Mecca”, along with implicit complaints that point to the manipulation of religious and national emotions.<\/span><\/p>\n

By analysing the keywords in the negative discourse, we found that the most frequent words were: (Umrah pilgrims, Egyptians, tourism, food, sleeping on the ground, begging, thefts), in addition to other words expressing poverty, poor organisation, humiliation, suffering and loss of dignity, and the presence of terms such as “exploitation” and “money” that contained implicit accusations. We also found indicators of systematic incitement through the stereotyped repetition of phrases and sentences, as appeared in the word analysis, with a high focus on a specific nationality, namely (Egyptian), which may indicate an attempt to incite or steer public opinion, with religious contexts and emotional charging included to frame the complaint in a sensitive mould.<\/span><\/p>\n

The discourse analysis shows a systematic linguistic construction that reinforces a general discourse with three pillars: personalising responsibility (tourism, the minister, the state), tragic portrayal (sleeping on the ground, begging, regrettable, thefts), and invoking Egyptian and religious identity (Egypt, Umrah pilgrims, the Haram, Mecca). The parties targeted in the discourse included: the Saudi authorities, through references to problems in the Haram or with Umrah; the Egyptian government or the Egyptian Ministry of Tourism, through words such as “tourism” and “Egyptian”, in a way that links them to failure or complicity; and Umrah organising companies were among the parties blamed in the texts of the tweets.<\/span><\/p>\n

 <\/p>\n

\"\"<\/h3>\n

Indicators of content engineering<\/b><\/h1>\n

We detected indicators of content engineering through: intensive retweeting and reposting of links, which indicates the transfer and repetition of the same content across multiple accounts; and the repetition of the same linguistic structure and terms, such as “Egyptian Umrah pilgrims”, “sleeping on the ground”, “begging” and “theft”, in hundreds of tweets, which suggests the use of ready-made templates for repeated posting (bot-like behavior). The account name alnaif_969@ was also repeated, appearing 481 times, indicating that it may be one of the pivotal accounts or one that was targeted by being linked to the campaign.<\/span><\/p>\n

By monitoring the accounts most active in spreading negative discourse, we noticed that there are accounts that each posted between 10 and 22 negative posts, with almost no positive content, the most prominent being: @_900_900, @111104427l1ahnl, @cookingarba1, @hamdamhamd3. We also found that the behaviour of some accounts is identical in terms of the number of posts, the share of negative discourse and the repetition of vocabulary, which suggests that they are either bots (automated accounts) or paid or directed accounts within a specific influence network, in addition to the fact that some accounts are Saudi and some are from Egypt or of unknown nationality, which makes cross-border coordination possible.<\/span><\/p>\n

Most of the accounts active in the negative discourse appear to be based in Saudi Arabia, and most of the attack was directed against Egyptian Umrah pilgrims in Mecca. There are suspicions that some of these accounts belong to a “coordinated Saudi network” used to target specific parties through sudden campaigns. The campaign appears aimed at tarnishing the image of Egyptians in Mecca and focusing on alleged negative behaviours such as begging, theft, poor food and chaos, with the repetition of extremely negative vocabulary, indicating deliberate amplification or framing of a stereotype.<\/span><\/p>\n

By analysing textual similarity (semantic similarity) between the accounts’ posts using the Python programming language, we found that online accounts on “X” such as @_900_900, @ezalklam and others record relatively high textual similarity (average similarity up to 0.32), with a high standard deviation as well. High textual similarity means that the content is recycled, copied or managed by a single party, while a wide range in the standard deviation indicates the use of different forms of wording for the same meaning, that is, an attempt to bypass repetition-detection algorithms.<\/span><\/p>\n

To analyse the semantic data of the influential accounts and their relationship to the countries from which they operate, we used Python to calculate average similarity (similarity avg), the standard deviation score and the highest similarity, and found that the highest similarity score belonged to the Saudi account @_900_900, which recorded <\/b>0.947, with a standard deviation score of 0.256 and an average similarity of 0.327. The account @ezalklam, whose country is not stated, came second in highest similarity score, at 1.000, with a standard deviation of 0.365 and an average similarity of 0.268. The Egyptian account @shaheey came third in terms of standard deviation score, at 0.183, with a standard deviation score of 0.049 and an average similarity of 0.093. In fourth place was the Saudi account @abdullah1383_, with a similarity score of 0.133, a standard deviation score of 0.032 and an average similarity of 0.052, and in fifth place was the Bahraini account @alkhayariamor, which recorded a similarity score of 0.581, a standard deviation of 0.095 and an average similarity of 0.065.<\/span><\/p>\n

The results showed that the Saudi account @_900_900 is the most negative and the highest in similarity with the related general content, and that most accounts with prominent negative influence come from Egypt, Saudi Arabia and some Gulf states such as Bahrain, which may indicate that the discussion spread on a regional and not merely local scale. Accounts with low average similarity (such as @shaheey from Egypt) tend to write content less consistent with the rest of the wave, which may reflect more independent or personal opinions. Saudi Arabia and Egypt appear as the most prominent sources of influential accounts, which may reflect the geography of the discussion, while the high level of similarity between the tweets of some users indicates the possibility of directed campaigns or the retweeting of popular content.<\/span><\/p>\n

\"\"<\/p>\n

Indicators of systematic incitement<\/b><\/h1>\n

The campaign used a humanitarian and religious entry point to win sympathy, but it quickly turns into an accusatory political or defamatory discourse targeting the Egyptian authorities (holding them responsible for the failure to organise Umrah), the Saudi authorities (for poor organisation or treatment), and tourism companies and intermediaries (as a tool of exploitation). These indicators point to the possibility of a systematic online campaign aimed at: tarnishing a particular image (of a party or a country), manufacturing angry public opinion using online amplification tools such as fake or recycled accounts, and exploiting the emotional nature of the topic to fuel engagement and media pressure.<\/span><\/p>\n

In searching for indicators of systematic incitement, it emerged that offensive\/accusatory vocabulary was clearly repeated (exploitation, money), along with repeated keywords suggesting a unified narrative and temporal synchronisation at the peak, such as “Egyptian Umrah pilgrims”, “sleeping on the ground” and “begging”, as March saw a sudden explosion, and the retweet rate was abnormally high, making up roughly 58% of the negative tweets. Given that the vast majority of negative tweets originated from one particular country, there are strong indicators of a systematic and coordinated negative discourse, whether it resulted from a spontaneous campaign driven by a position or an event, or was deliberately steered by entities or groups to influence public opinion, especially through repeating messages, invoking national identity and building a regrettable narrative that fuels anger.<\/span><\/p>\n

The findings of this investigation reveal the features of a systematic digital incitement campaign that targeted Egyptian Hajj and Umrah pilgrims, exploiting religious and emotional contexts and loaded with intensive, directed negative discourse. The organised timing, the stereotyped repetition of hashtags and vocabulary, and the concentration of activity in specific accounts are all strong indicators of clear coordination that goes beyond spontaneous interactions or individual opinions.<\/span><\/p>\n

Although the intensity of the discourse has declined in recent months, its impact is still present in the structure of digital discussions related to Hajj, with some symbols and terms still in circulation. By tracking the data and analysing the patterns, it becomes clear that the campaign was not merely a passing outburst of anger but part of a broader discourse that is reproduced whenever the Hajj season approaches or a crisis related to it erupts.<\/span><\/p>\n

This campaign raises bigger questions about the role of digital platforms in facilitating the spread of hate speech, and about the mechanisms of digital intervention to inflame public opinion through religious and national identity. While the identity of the actors remains in the shadows, the investigation highlights the urgent need to understand the hidden structure behind these campaigns and to work on developing tools for digital monitoring and accountability, to protect users from systematic polarisation and incitement, particularly in issues linked to religious rites and sacred matters.<\/span><\/p>\n

 <\/p>\n

(This investigation was produced with the support of the Arab Fact-Checkers Hub (AFH))<\/span><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

A systematic incitement campaign against Egyptian Hajj and Umrah pilgrims on “X”, including thousands of negative tweets and showing indicators of prior coordination and of disinformation using religious and national identity.<\/p>\n","protected":false},"author":4,"featured_media":13059,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"footnotes":""},"categories":[410],"tags":[],"kateb":[1550],"class_list":["post-16955","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-investigations-en","kateb-aya-yasser"],"jetpack_featured_media_url":"https:\/\/zawia3.com\/wp-content\/uploads\/2025\/06\/\u0627\u0644\u062d\u062c\u0627\u062c-\u0627\u0644\u0645\u0635\u0631\u064a\u064a\u0646.png","_links":{"self":[{"href":"https:\/\/zawia3.com\/en\/wp-json\/wp\/v2\/posts\/16955","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/zawia3.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/zawia3.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/zawia3.com\/en\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/zawia3.com\/en\/wp-json\/wp\/v2\/comments?post=16955"}],"version-history":[{"count":5,"href":"https:\/\/zawia3.com\/en\/wp-json\/wp\/v2\/posts\/16955\/revisions"}],"predecessor-version":[{"id":23148,"href":"https:\/\/zawia3.com\/en\/wp-json\/wp\/v2\/posts\/16955\/revisions\/23148"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/zawia3.com\/en\/wp-json\/wp\/v2\/media\/13059"}],"wp:attachment":[{"href":"https:\/\/zawia3.com\/en\/wp-json\/wp\/v2\/media?parent=16955"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/zawia3.com\/en\/wp-json\/wp\/v2\/categories?post=16955"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/zawia3.com\/en\/wp-json\/wp\/v2\/tags?post=16955"},{"taxonomy":"kateb","embeddable":true,"href":"https:\/\/zawia3.com\/en\/wp-json\/wp\/v2\/kateb?post=16955"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}