{"id":124,"date":"2026-10-13T08:03:12","date_gmt":"2026-10-13T08:03:12","guid":{"rendered":"https:\/\/blog.araboost.com\/micro-influencer-fraud-exposed-how-fake-followers-and-inflated-engagement-are-deceiving-brands\/"},"modified":"2026-10-13T08:03:12","modified_gmt":"2026-10-13T08:03:12","slug":"micro-influencer-fraud-exposed-how-fake-followers-and-inflated-engagement-are-deceiving-brands","status":"publish","type":"post","link":"https:\/\/blog.araboost.com\/en\/micro-influencer-fraud-exposed-how-fake-followers-and-inflated-engagement-are-deceiving-brands\/","title":{"rendered":"Micro-Influencer Fraud Exposed: How Fake Followers and Inflated Engagement Are Deceiving Brands"},"content":{"rendered":"<h1>Micro-Influencer Fraud: How to Spot Fake Followers, Inflated Engagement, and Protect Your Brand<\/h1>\n<p>Are you vetting creators thoroughly? If your team chooses partners based on surface-level numbers, your next influencer marketing campaign could rest on fake followers, inflated engagement, and weak audience credibility. In a market where brand trust is earned slowly and lost quickly, authentic influence is not just a performance issue. It is a business decision that affects efficiency, reputation, and long-term results.<\/p>\n<p>This guide is built for brands, marketers, and campaign managers who need a sharper way to check if an influencer is authentic before signing a deal. Each section explains what to look for, why it matters, and how to respond with confidence.<\/p>\n<h2>What Micro-Influencer Fraud Means and Why It Matters<\/h2>\n<p>Micro-influencer fraud is the artificial inflation of a creator\u2019s perceived value through manipulated follower counts, engagement signals, or audience quality. That is different from ordinary underperformance. A campaign can miss expectations for legitimate reasons, such as weak creative, poor timing, or unclear messaging. Fraud begins when the signals used to evaluate the creator are misleading from the start.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> A creator appears strong on paper but produces little real business impact. <strong>Explanation:<\/strong> Micro-influencer fraud often disguises itself as niche influence, making weak accounts look commercially credible. <strong>Action:<\/strong> Separate poor execution from false audience signals before judging campaign results.<\/li>\n<li><strong>Observation:<\/strong> Smaller accounts are often assumed to be safer than larger creators. <strong>Explanation:<\/strong> That assumption is risky because manipulation scales easily, even with modest audiences. A few thousand fake followers can significantly distort a micro-influencer profile. <strong>Action:<\/strong> Apply the same authenticity audit standards to micro-creators that you would use for larger partnerships.<\/li>\n<li><strong>Observation:<\/strong> Teams focus on efficiency and overlook audience authenticity. <strong>Explanation:<\/strong> Fraud at the micro level can quietly drain spend across multiple partnerships and weaken ROI. <strong>Action:<\/strong> Treat creator vetting as a strategic investment decision, not an administrative step.<\/li>\n<\/ul>\n<h2>How Fake Followers Are Bought or Generated<\/h2>\n<p>Fake followers rarely appear by chance. In most cases, they are purchased or generated through systems designed to inflate audience size without improving real reach, relevance, or conversion potential.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> Follower counts rise while reach and impressions stay weak. <strong>Explanation:<\/strong> Purchased followers do not behave like real audiences. They add volume without adding attention. <strong>Action:<\/strong> Compare total followers with average reach per post and story before approving a creator.<\/li>\n<li><strong>Observation:<\/strong> Many followers look empty, inactive, or strangely uniform. <strong>Explanation:<\/strong> Fake followers are often bot accounts, recycled profiles, inactive accounts, or click-farm-generated identities. <strong>Action:<\/strong> Sample follower lists manually and check for profile photos, posting history, bios, and visible signs of human behavior.<\/li>\n<li><strong>Observation:<\/strong> Audience growth seems too fast for the quality or consistency of the content. <strong>Explanation:<\/strong> Account inflation services can deliver follower bursts that create the appearance of momentum. <strong>Action:<\/strong> Review follower growth patterns over time instead of trusting a single follower count.<\/li>\n<\/ul>\n<h2>How Inflated Engagement Is Manufactured<\/h2>\n<p>Inflated engagement is often the second layer of deception. Once follower counts are padded, likes, comments, saves, and shares may also be manipulated to make the audience appear active and responsive.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> Engagement looks high, but comments feel repetitive or disconnected from the content. <strong>Explanation:<\/strong> Engagement fraud is commonly produced through engagement pods, coordinated groups, or automated activity that simulates enthusiasm. <strong>Action:<\/strong> Read comments closely and assess whether they show relevance, variety, and genuine conversation.<\/li>\n<li><strong>Observation:<\/strong> Posts receive similar volumes of interaction regardless of topic, quality, or format. <strong>Explanation:<\/strong> Real audiences react unevenly. Artificial systems often produce suspiciously stable interaction patterns. <strong>Action:<\/strong> Compare engagement across multiple posts instead of relying on one strong example.<\/li>\n<li><strong>Observation:<\/strong> Likes are high, but thoughtful replies, shares, and saves remain low. <strong>Explanation:<\/strong> Inflated engagement can create the illusion of influence while hiding weak audience authenticity. <strong>Action:<\/strong> Prioritize depth metrics that suggest intent over vanity metrics that merely suggest visibility.<\/li>\n<\/ul>\n<h2>The Business Risks of Believing Fake Metrics<\/h2>\n<p>Fraud does not remain a creator problem for long. The moment manipulated numbers influence partner selection, budget allocation, or performance expectations, it becomes a brand problem.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> Campaign spend goes to creators who fail to move traffic or sales. <strong>Explanation:<\/strong> Fake followers and inflated engagement reduce conversion rate and weaken ROI because the audience is either not real or not relevant. <strong>Action:<\/strong> Tie creator selection to measurable outcomes such as qualified clicks, traffic quality, and conversions.<\/li>\n<li><strong>Observation:<\/strong> Media planning decisions are based on false benchmarks. <strong>Explanation:<\/strong> Fraud distorts influencer selection by making weak creators appear comparable to stronger ones. <strong>Action:<\/strong> Build historical performance baselines using verified campaign data, not creator-reported screenshots alone.<\/li>\n<li><strong>Observation:<\/strong> A partnership creates discomfort or reputational risk after launch. <strong>Explanation:<\/strong> Brand safety issues emerge when brands align with creators whose audience credibility, ethics, or disclosure practices are questionable. <strong>Action:<\/strong> Make trust and transparency part of the selection process from the beginning.<\/li>\n<\/ul>\n<h2>Genuine Niche Influence vs Manipulated Metrics<\/h2>\n<p>Not every small creator with modest numbers is weak, and not every creator with fast growth is fraudulent. The real challenge is telling the difference between authentic niche authority and manufactured momentum.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> A creator has a small but active and clearly defined audience. <strong>Explanation:<\/strong> Genuine niche influence often produces stronger relevance, better conversation quality, and higher conversion potential than a larger inflated audience. <strong>Action:<\/strong> Favor audience credibility and alignment over scale alone.<\/li>\n<li><strong>Observation:<\/strong> Engagement fluctuates naturally by topic and format. <strong>Explanation:<\/strong> Healthy engagement patterns reflect real human response, while manipulated metrics often show suspicious spikes or ratios detached from content quality. <strong>Action:<\/strong> Review several weeks of content to understand normal performance variation.<\/li>\n<li><strong>Observation:<\/strong> The creator\u2019s community shows trust through nuanced interaction. <strong>Explanation:<\/strong> Authentic influence looks like recognition, discussion, repeat commenters, and topic expertise. <strong>Action:<\/strong> Look for signs of relationship depth, not just reach volume.<\/li>\n<\/ul>\n<h2>Warning Signs Brands Should Look For<\/h2>\n<p>Red flags rarely appear one at a time. Fraud risk becomes much clearer when multiple warning signs cluster together.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> Follower growth patterns show sudden surges without an obvious catalyst. <strong>Explanation:<\/strong> Purchased growth often appears in abrupt spikes rather than steady audience accumulation. <strong>Action:<\/strong> Ask what caused the increase and request evidence such as collaborations, media exposure, or paid promotion details.<\/li>\n<li><strong>Observation:<\/strong> Comment sections are filled with generic praise, emoji-only replies, or repeated phrasing. <strong>Explanation:<\/strong> Suspicious comment quality is a common sign of engagement fraud. <strong>Action:<\/strong> Check whether comments refer to the actual content or could be copied onto almost any post.<\/li>\n<li><strong>Observation:<\/strong> Audience demographics do not match the creator\u2019s claimed niche or market. <strong>Explanation:<\/strong> A niche creator with followers concentrated in irrelevant geographies may have weak audience authenticity or weak audience fit. <strong>Action:<\/strong> Review audience demographics, language patterns, and regional relevance before moving forward.<\/li>\n<li><strong>Observation:<\/strong> Reach is erratic, and engagement rate swings wildly without explanation. <strong>Explanation:<\/strong> Inconsistent performance can signal artificial activity, algorithmic distortion caused by poor audience quality, or off-platform manipulation. <strong>Action:<\/strong> Audit trends across posts, stories, and previous branded content.<\/li>\n<li><strong>Observation:<\/strong> Posting behavior feels repetitive and overly transactional. <strong>Explanation:<\/strong> Accounts built mainly for monetization often show weaker community trust. <strong>Action:<\/strong> Review the content mix for originality, consistency, and credible niche positioning.<\/li>\n<\/ul>\n<h2>How to Check If an Influencer Audience Is Real<\/h2>\n<p>To check if an influencer is authentic, combine profile review, audience analysis, and interaction quality checks. No single signal is strong enough on its own.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> The profile is incomplete or strategically vague. <strong>Explanation:<\/strong> Thin bios, inconsistent identity cues, and limited activity history can indicate a low-investment account built for appearance rather than influence. <strong>Action:<\/strong> Review profile completeness, archive depth, platform consistency, and evidence of a real creator identity.<\/li>\n<li><strong>Observation:<\/strong> Follower-to-following balance seems unnatural for the creator\u2019s stage. <strong>Explanation:<\/strong> Some inflated accounts follow large volumes of users to stimulate reciprocal growth or disguise weak organic traction. <strong>Action:<\/strong> Evaluate the ratio in context, especially when follower counts are high but authority signals are weak.<\/li>\n<li><strong>Observation:<\/strong> Audience demographics appear broad but commercially irrelevant. <strong>Explanation:<\/strong> Audience authenticity is not only about whether followers are real people. It is also about whether they match your market. <strong>Action:<\/strong> Check geography, age range, language, and niche alignment against your campaign goals.<\/li>\n<li><strong>Observation:<\/strong> Interactions lack continuity. <strong>Explanation:<\/strong> Real communities usually have recurring names, layered conversations, and evolving relationships. <strong>Action:<\/strong> Look for repeat participants and meaningful discussion across multiple posts.<\/li>\n<\/ul>\n<h2>Metrics to Audit Before Launching an Influencer Marketing Campaign<\/h2>\n<p>The right metrics should reveal influence, not just visibility. A disciplined audit protects spend and improves decision-making before a campaign goes live.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> The creator emphasizes follower count and likes. <strong>Explanation:<\/strong> These are incomplete indicators and relatively easy to manipulate. <strong>Action:<\/strong> Audit reach, impressions, engagement rate, saves, shares, clicks, traffic quality, and conversion rate.<\/li>\n<li><strong>Observation:<\/strong> Story performance or link activity is missing from the discussion. <strong>Explanation:<\/strong> Click behavior often reveals stronger commercial intent than feed engagement alone. <strong>Action:<\/strong> Request recent examples of outbound traffic and downstream performance where available.<\/li>\n<li><strong>Observation:<\/strong> One campaign result is used as proof of ongoing effectiveness. <strong>Explanation:<\/strong> A single success may be an outlier. Historical consistency matters more than a snapshot. <strong>Action:<\/strong> Compare performance across several campaigns or time periods.<\/li>\n<li><strong>Observation:<\/strong> Engagement rate is presented without context. <strong>Explanation:<\/strong> A healthy engagement rate means little if impressions are low quality or traffic does not convert. <strong>Action:<\/strong> Connect engagement rate to reach, audience relevance, and post-click behavior.<\/li>\n<\/ul>\n<h2>How to Read Follower Growth Patterns Over Time<\/h2>\n<p>Trend analysis often reveals what static metrics hide. Organic growth has texture. Inorganic growth usually leaves visible traces.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> Growth follows a steady upward curve with occasional explainable peaks. <strong>Explanation:<\/strong> This is more consistent with healthy creator development driven by content, collaborations, or visibility. <strong>Action:<\/strong> Ask for the context behind peak periods and confirm that it aligns with visible activity.<\/li>\n<li><strong>Observation:<\/strong> The account shows spikes, plateaus, and repeated bursts with no clear story behind them. <strong>Explanation:<\/strong> That pattern may indicate purchased followers, giveaway distortions, or poor-quality third-party promotion. <strong>Action:<\/strong> Investigate each spike and assess whether the new audience remained active afterward.<\/li>\n<li><strong>Observation:<\/strong> Large audience jumps do not lead to stronger reach or more meaningful comments. <strong>Explanation:<\/strong> Real growth usually changes performance behavior, while inorganic growth often changes only the headline number. <strong>Action:<\/strong> Compare growth periods against engagement and impressions to test legitimacy.<\/li>\n<\/ul>\n<h2>How to Evaluate Comment Quality and Conversation Signals<\/h2>\n<p>Comment sections offer one of the clearest views into influencer authenticity. Numbers can be bought. Real conversation is much harder to fake at scale.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> Comments are generic, repetitive, or unrelated to the content. <strong>Explanation:<\/strong> Phrases such as \u201cnice post\u201d repeated by multiple accounts can signal low-value interaction or automation. <strong>Action:<\/strong> Manually inspect several posts and estimate the share of specific versus generic comments.<\/li>\n<li><strong>Observation:<\/strong> Most replies are emoji-only or formulaic. <strong>Explanation:<\/strong> Real communities usually show at least some thoughtful reactions, questions, or personal references. <strong>Action:<\/strong> Evaluate comments, saves, shares, and creator replies together when judging engagement quality.<\/li>\n<li><strong>Observation:<\/strong> The creator rarely responds or extends the conversation. <strong>Explanation:<\/strong> Authentic communities often involve reciprocal dialogue, which strengthens trust and brand transfer. <strong>Action:<\/strong> Prioritize creators who nurture discussion rather than simply collecting shallow signals.<\/li>\n<\/ul>\n<h2>Using Fraud Detection Tools and Manual Vetting Together<\/h2>\n<p>Technology can speed up screening, but it should not replace human judgment. The strongest creator vetting systems combine both.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> Platform dashboards or fraud detection tools flag unusual audience clusters. <strong>Explanation:<\/strong> These tools can identify bot accounts, suspicious audience credibility patterns, and anomalies in geography or engagement. <strong>Action:<\/strong> Use tool-based scoring as an early warning system, not a final verdict.<\/li>\n<li><strong>Observation:<\/strong> The data appears acceptable, but brand fit still feels uncertain. <strong>Explanation:<\/strong> Tools cannot fully measure tone, trust, values, or creative integrity. <strong>Action:<\/strong> Add manual review for messaging quality, community alignment, and reputational fit.<\/li>\n<li><strong>Observation:<\/strong> Your team needs scale without losing precision. <strong>Explanation:<\/strong> A hybrid review process is usually the most reliable approach for authenticity audits. <strong>Action:<\/strong> Consider structured influencer discovery and campaign management platforms that support screening, performance estimation, and more consistent workflow.<\/li>\n<\/ul>\n<h2>A Practical Vetting Checklist for Brands<\/h2>\n<p>Use this sequence before any partnership decision to keep your process disciplined and repeatable.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> Profile review is often rushed. <strong>Explanation:<\/strong> Surface impressions can hide weak fundamentals. <strong>Action:<\/strong> Check identity clarity, niche consistency, posting history, bio quality, and platform maturity.<\/li>\n<li><strong>Observation:<\/strong> Content review focuses only on aesthetics. <strong>Explanation:<\/strong> Strong visuals without community trust create a weak commercial asset. <strong>Action:<\/strong> Assess relevance, originality, storytelling, disclosure habits, and evidence of genuine audience resonance.<\/li>\n<li><strong>Observation:<\/strong> Audience review is limited to screenshots. <strong>Explanation:<\/strong> Self-reported media kits can leave out risk signals. <strong>Action:<\/strong> Validate audience demographics, geography, language, and likely buyer fit independently wherever possible.<\/li>\n<li><strong>Observation:<\/strong> Metric review overweights likes and underweights outcomes. <strong>Explanation:<\/strong> Vanity growth does not guarantee commercial influence. <strong>Action:<\/strong> Review reach, impressions, engagement rate, saves, shares, clicks, traffic quality, and conversion signals.<\/li>\n<li><strong>Observation:<\/strong> Teams struggle to decide when evidence is mixed. <strong>Explanation:<\/strong> Without a framework, subjective bias often takes over. <strong>Action:<\/strong> Use a clear go or no-go rule: proceed only if audience authenticity, content quality, brand fit, and metric credibility all meet your threshold.<\/li>\n<\/ul>\n<h2>Questions to Ask Creators Before Signing a Partnership<\/h2>\n<p>The right questions encourage transparency without sounding accusatory. Serious creators usually respect disciplined buyers.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> Audience composition is described in broad terms. <strong>Explanation:<\/strong> Broad claims can hide weak relevance. <strong>Action:<\/strong> Ask for audience demographics, top geographies, language mix, and the share of followers that match your target market.<\/li>\n<li><strong>Observation:<\/strong> Past campaign performance is summarized vaguely. <strong>Explanation:<\/strong> Verbal assurances are not enough for budget decisions. <strong>Action:<\/strong> Request evidence from previous partnerships, including reach, clicks, conversions, or other agreed outcomes.<\/li>\n<li><strong>Observation:<\/strong> Growth has accelerated suddenly. <strong>Explanation:<\/strong> This may be legitimate, but it requires context. <strong>Action:<\/strong> Ask whether growth came from paid promotion, giveaways, collaborations, or third-party traffic sources.<\/li>\n<li><strong>Observation:<\/strong> Defensive answers appear when audience quality is discussed. <strong>Explanation:<\/strong> Trustworthy creators usually welcome professional scrutiny. <strong>Action:<\/strong> Favor evidence-based responses over confidence alone.<\/li>\n<\/ul>\n<h2>Contracting and Monitoring to Reduce Fraud Risk<\/h2>\n<p>Even strong vetting should be reinforced with clear agreements and early campaign monitoring.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> Contracts focus on deliverables but ignore quality thresholds. <strong>Explanation:<\/strong> Without defined expectations, it is harder to challenge low-value traffic or suspicious engagement after launch. <strong>Action:<\/strong> Include disclosure requirements, performance definitions, reporting terms, and remedies for material misrepresentation.<\/li>\n<li><strong>Observation:<\/strong> Early results look active but commercially weak. <strong>Explanation:<\/strong> Inflated engagement can appear immediately while quality traffic remains absent. <strong>Action:<\/strong> Monitor early clicks, session quality, bounce behavior, and conversion rate before scaling spend.<\/li>\n<li><strong>Observation:<\/strong> Teams wait until the campaign ends to review authenticity concerns. <strong>Explanation:<\/strong> Late review limits recovery options. <strong>Action:<\/strong> Set checkpoints at launch, mid-campaign, and completion to protect ROI.<\/li>\n<\/ul>\n<h2>Building a Safer Influencer Selection Process Going Forward<\/h2>\n<p>Strong brands do not rely on instinct alone. They build systems that turn judgment into repeatable operational discipline.<\/p>\n<ul>\n<li><strong>Observation:<\/strong> Vetting quality varies by team member or campaign. <strong>Explanation:<\/strong> Inconsistent standards lead to inconsistent outcomes. <strong>Action:<\/strong> Create a repeatable creator vetting framework with scoring criteria for authenticity, relevance, safety, and performance.<\/li>\n<li><strong>Observation:<\/strong> Lessons from past campaigns are not centralized. <strong>Explanation:<\/strong> Without benchmark data, teams repeat avoidable mistakes. <strong>Action:<\/strong> Maintain records on reach, impressions, engagement concerns, traffic quality, and ROI by creator.<\/li>\n<li><strong>Observation:<\/strong> Authenticity is treated only as risk management. <strong>Explanation:<\/strong> In practice, it is also a competitive advantage. Credibility compounds over time. <strong>Action:<\/strong> Make audience authenticity part of your long-term brand operating model, not just campaign hygiene.<\/li>\n<\/ul>\n<h2>Conclusion: Protecting Campaign Performance by Prioritizing Authenticity<\/h2>\n<p>Micro-influencer fraud distorts the signals brands rely on to make smart partnership decisions. Fake followers, inflated engagement, bot accounts, click farms, and audience mismatches can all make a creator appear more influential than they really are. The right response is not cynicism. It is discipline. When you define fraud clearly, review follower growth patterns, evaluate suspicious comment quality, audit reach and impressions, verify audience demographics, and combine fraud detection tools with manual judgment, you protect both campaign performance and brand trust.<\/p>\n<p>Authentic creators may not always be the loudest, but they are often the most valuable. They build real communities, create credible conversation, and deliver the kind of attention that supports stronger conversion rates, better ROI, and more durable brand equity.<\/p>\n<h2>Frequently Asked Questions<\/h2>\n<h3>What is micro-influencer fraud?<\/h3>\n<p>Micro-influencer fraud is a form of manipulation in which a creator inflates follower counts, engagement, or audience signals so they appear more influential than they really are.<\/p>\n<h3>How are fake followers bought or generated?<\/h3>\n<p>They are commonly purchased through services that use bot accounts, inactive profiles, recycled identities, or click-farm activity to raise follower totals without adding real audience value.<\/p>\n<h3>What is inflated engagement and how is it created?<\/h3>\n<p>Inflated engagement is artificial activity such as boosted likes, comments, saves, or shares, often produced through engagement pods, coordinated groups, or automated systems.<\/p>\n<h3>What are the biggest warning signs of fake audience credibility?<\/h3>\n<p>Common red flags include sudden follower spikes, generic comments, mismatched audience demographics, low-quality engagement, geographic anomalies, and suspicious growth patterns over time.<\/p>\n<h3>How can brands check if an influencer is authentic before partnering?<\/h3>\n<p>Brands can review audience demographics, follower growth patterns, engagement rate, profile history, comment quality, and interaction depth, then validate those findings with fraud detection tools and manual creator vetting.<\/p>\n<h3>Which metrics matter most before an influencer marketing campaign?<\/h3>\n<p>Before launching a campaign, brands should audit reach, impressions, engagement rate, saves, clicks, traffic quality, conversions, conversion rate, and ROI rather than relying only on follower count or likes.<\/p>\n<p>If creator vetting is weak, the cost is not just wasted budget. It is reduced trust, distorted planning, and avoidable risk to your brand.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Micro-Influencer Fraud: How to Spot Fake Followers, Inflated Engagement, and Protect Your Brand Are you vetting creators thoroughly? If your team chooses partners based on surface-level numbers, your next influencer marketing campaign could rest on fake followers, inflated engagement, and weak audience credibility. In a market where brand trust is earned slowly and lost quickly, [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":122,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-124","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry"],"_links":{"self":[{"href":"https:\/\/blog.araboost.com\/en\/wp-json\/wp\/v2\/posts\/124","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.araboost.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.araboost.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.araboost.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.araboost.com\/en\/wp-json\/wp\/v2\/comments?post=124"}],"version-history":[{"count":0,"href":"https:\/\/blog.araboost.com\/en\/wp-json\/wp\/v2\/posts\/124\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blog.araboost.com\/en\/wp-json\/wp\/v2\/media\/122"}],"wp:attachment":[{"href":"https:\/\/blog.araboost.com\/en\/wp-json\/wp\/v2\/media?parent=124"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.araboost.com\/en\/wp-json\/wp\/v2\/categories?post=124"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.araboost.com\/en\/wp-json\/wp\/v2\/tags?post=124"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}