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Channel

菲龙网头条报道@Feilong

@feilong

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry

53,647subscribers

-6,646 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1002040225208
TypeChannel
Username@feilong
Description🇨🇿菲龙网官方媒体频道 @feilong ("菲龙"全拼)中文媒体,发布本地新闻,博彩资讯、当地美食、旅游攻略、等便民讯息。
CreatedBetween 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live5 September 2026
Measurements held26
Confirmed unchanged1 time, most recently 5 September 2026
On Telegramt.me/feilong

Topic

Local community — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 2026 and assigned it the closest of 31 fixed categories, at 69% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear word for word on 7 other registered channels. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (6 of the pairs behind the counts below)
Posted firstThenOverlapGap
@yatai1/193616 Aug 2026, 13:30 UTC@feilong/28023 · this entry6 Aug 2026, 13:30 UTC1.00under a minute
@yatai1/193706 Aug 2026, 13:57 UTC@feilong/28032 · this entry6 Aug 2026, 13:57 UTC1.00under a minute
@yatai1/193726 Aug 2026, 14:30 UTC@feilong/28034 · this entry6 Aug 2026, 14:30 UTC1.00under a minute
@feilong/28036 · this entry6 Aug 2026, 14:34 UTC@yatai1/193746 Aug 2026, 14:34 UTC1.00under a minute
@yatai1/193766 Aug 2026, 14:35 UTC@feilong/28038 · this entry6 Aug 2026, 14:35 UTC1.00under a minute
@feilong/28041 · this entry6 Aug 2026, 15:01 UTC@yatai1/193796 Aug 2026, 15:01 UTC1.00under a minute
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@yatai129 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (272)
@ytxw26 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (233)
@yatai225 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (223)
@xigang8I824 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (204)
@dibai717 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (161)
@guancha9 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (81)
@mlxy7 (7/7 hand-verifiable sample passed)1.00under a minutethis entry (61)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 15 of the 15 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.

“Published first” means first in this corpus. We hold 29 comparable posts for this entry, running 6 August 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Across the whole group of 8, the earliest publisher we hold is @yatai2. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_source, last confirmed 7 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Also posting the same content

This channel’s posts match, word for word or near enough, posts on 7 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.

Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

49,10662,59555,850.57 August 2026 — 60,293 subscribers8 August 2026 — 60,087 subscribers9 August 2026 — 59,914 subscribers10 August 2026 — 59,653 subscribers11 August 2026 — 59,484 subscribers12 August 2026 — 59,358 subscribers13 August 2026 — 59,117 subscribers14 August 2026 — 58,921 subscribers16 August 2026 — 58,083 subscribers17 August 2026 — 57,829 subscribers18 August 2026 — 57,542 subscribers19 August 2026 — 57,131 subscribers20 August 2026 — 56,259 subscribers21 August 2026 — 49,708 subscribers23 August 2026 — 49,106 subscribers24 August 2026 — 59,810 subscribers26 August 2026 — 62,595 subscribers26 August 2026 — 62,142 subscribers27 August 2026 — 61,798 subscribers28 August 2026 — 61,239 subscribers29 August 2026 — 60,438 subscribers30 August 2026 — 59,574 subscribers31 August 2026 — 58,695 subscribers2 September 2026 — 58,048 subscribers3 September 2026 — 55,066 subscribers5 September 2026 — 53,647 subscribers53,6477 August 20265 September 2026
26 measurements spanning 29 days, net -6,646. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 47,083–64,618 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 26
Measured (UTC)SubscribersChange
5 Sept 2026, 03:3953,647-1,419
3 Sept 2026, 09:4355,066-2,982
2 Sept 2026, 00:5858,048-647
31 Aug 2026, 23:4858,695-879
30 Aug 2026, 21:4559,574-864
29 Aug 2026, 19:4660,438-801
28 Aug 2026, 18:1461,239-559
27 Aug 2026, 21:0261,798-344
26 Aug 2026, 23:2462,142-453
26 Aug 2026, 01:3462,595+2,785
24 Aug 2026, 23:5859,810+10,704
23 Aug 2026, 13:0649,106-602
21 Aug 2026, 23:2749,708-6,551
20 Aug 2026, 15:0856,259-872
19 Aug 2026, 13:1157,131-411
18 Aug 2026, 12:1657,542-287
17 Aug 2026, 14:2857,829-254
16 Aug 2026, 05:3558,083-838
14 Aug 2026, 14:1858,921-196
13 Aug 2026, 08:1559,117first reading

Engagement

516 posts held, back to 6 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 65 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
0.206%
avg views ÷ 53,647 subscribers
Avg views / post
110
487 posts measured
Reaction rate
0%
reactions ÷ views · ER floor
Posts in window
487
of 516 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 1 of 487 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 5 September 2026
Posts held516 (6 August 20265 September 2026)
Views total53,768
Reactions total0
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken6 Sept 2026, 20:33 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Photos
24,300
Videos
5,110
Links
14,500

Lifetime counters from Telegram’s own channel header, read 6 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
1h 56m
Average length
51s

Measured directly from 138 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no mark.

Recent posts

5 Sept 2026, 14:24 UTC≈3,330 viewsread 6 September 2026
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香港警方开展大规模反诈专项行动,一共拘捕269人,涉案总金额高达3.2亿港元 这次行动从8月24日持续到9月2日,一共破获203宗案件,包含电话诈骗、网购骗局、网络投资诈骗等多种类型。 很多骗子伪装成支付平台、快递公司的客服,谎称包裹派送失败、账户存在异常,以此作为借口,一步步诱导受害人落入圈套。 警方特别提醒,港漂群体是这类诈骗的重点目标人群。后续警方还会联合通讯管理部门持续推进反诈工作,保护在港读书、工作人士的财产安全。 ———————————————— 📣欢迎加入东南亚华人交流群 🔗 https://t.me/dnyhr0 📣西港日记/柬埔寨新闻资讯 🔗:https://t.me/xigang8I8 ✅广告招商投稿澄清爆料: @jpz8i8

5 Sept 2026, 14:23 UTC≈3,950 viewsread 6 September 2026
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#赌场黑幕:石锤赌场杀猪 别说这些大赌场没有作弊 包有的 不然一晚上怎么杀你几百万上千万美金? 那些输几千万上亿的老板们,不知道看完你们作何感想?每次被点杀,每次开8点就以为稳了,但是总能在让你看到8输9 看完这个 老板们 你们还敢去这些所谓的大赌场玩吗?现在知道为什么在赌场十赌九输了吧 这就好比如我们一起来玩石头剪刀布 你赢了赌场给你500万 但是提前是你先出拳 赌场后出拳 (为什么很多赌场都是你先下注 在发牌😂) ———————————————— 📣欢迎加入东南亚华人交流群 🔗 https://t.me/dnyhr0 📣西港日记/柬埔寨新闻资讯 🔗:https://t.me/xigang8I8 ✅广告招商投稿澄清爆料: @jpz8i8

5 Sept 2026, 14:23 UTC≈1,180 viewsread 6 September 2026
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#国内资讯:内蒙古一女子感觉时运不济找“大仙儿”转运,遭对方以“鬼附身”“家人将遭灾祸”恐吓,先后被骗转账近百万元 内蒙古自治区公安厅9月1日对外发布案件通报:今年1月5日,王女士、苏女士等多名受害人前往赤峰市公安局松山分局刑侦大队报案,称遭到梁某某以封建迷信的方式诈骗。接到报案后,分局立即开展侦办工作。 经查,2025年2月至10月,受害人王女士因生活不顺,自认时运不济,经他人介绍找到梁某某,希望借助其帮忙转运消灾。 梁某某通过焚香请仙上身塑造自身“身怀仙家”的人设,谎称自己能够消灾解难,又编造王女士被鬼怪缠身、家人即将遭遇灾祸、其母亲寿命堪忧等话术恐吓王女士,并以驱鬼、续命、化解灾厄为借口,多次向王女士索要高额法事费用。 受恐惧心理驱使,王女士先后向梁某某转账近百万元。 同一时期,苏女士等人因遭遇车祸、生意受挫,也前来找梁某某“看事”,同样被梁某某使用同类封建迷信说辞骗取钱财。 犯罪嫌疑人梁某某并无固定生活来源,

5 Sept 2026, 14:22 UTC≈2,970 viewsread 6 September 2026
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波贝宪兵捣毁两处毒赌窝点 68名涉案人员移送法办 近日,波贝市宪兵部队突袭两处涉嫌贩毒、容留吸毒及非法开设赌场据点,现场共控制133人。 经尿检与审讯,警方释放65名无涉案嫌疑人员,将确认涉案的68名嫌疑人(含48名女性)移交司法机关。 据披露,涉案人员包括39名柬籍人员及29名外籍人员(15名泰籍、7名中籍、4名越籍、2名老挝籍及1名印尼籍)。 今天下午,波贝宪兵已将嫌疑人连同查获的毒品、手机等物证一并移送省初级法院依法审理。 ———————————————— 📣欢迎加入东南亚华人交流群 🔗 https://t.me/dnyhr0 📣西港日记/柬埔寨新闻资讯 🔗:https://t.me/xigang8I8 ✅广告招商投稿澄清爆料: @jpz8i8

5 Sept 2026, 13:53 UTC≈3,610 viewsread 6 September 2026
Forwarded from @bbbb342424Photo

😀😀😀😀😀 😀😀😀😀😀😀😀😀 新会员注册首存 😀😀😀😀送😀😀😀 2存 3存再次赠送 (都只需1倍流水) 游戏爆率超高,期待你的加入。 😀全网独家,所有游戏返水无上限 😀上亿现金储备,100%出款 😀😀😀😀仅支持😀充值 😀😀😀😀:@kefu5 😀😀😀😀:@bolai9 😀😀😀😀:txyl.app 😀😀😀😀😀😀😀😀

5 Sept 2026, 13:52 UTC≈3,010 viewsread 6 September 2026
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#小姐姐投稿:金边三号安置点上演“东南亚友谊赛”印尼、老挝、越南妹妹开启巅峰对决! 平时大家都是姐妹相称,今天却因为一点小摩擦直接“火花四射”。印尼妹妹不服输,老挝妹妹不示弱,越南妹妹更是加入战局,现场气氛堪比东盟女子争霸赛。 不过大家都是漂泊在外的姐妹,吵归吵,闹归闹,别把友谊的小船直接掀翻了。三号安置点:没有硝烟的地方,也能天天上演连续剧。 ———————————————— 📣欢迎加入东南亚华人交流群 🔗 https://t.me/dnyhr0 📣西港日记/柬埔寨新闻资讯 🔗:https://t.me/xigang8I8 ✅广告招商投稿澄清爆料: @jpz8i8

5 Sept 2026, 13:52 UTC10 viewsread 6 September 2026
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#群友投稿:有些话,本来想给彼此留最后一点体面,现在看来没必要了。 这件事我忍到今天,不是因为我没话说,而是因为大家一起相处这么久,我一直觉得做人应该留条后路。可惜最后换来的只有四个字:人走茶凉。 金蛋,作为一个老板,出了事情以后逃避问题,工资问题迟迟不给解决,现在连消息都不回。更让我寒心的是,之前居然有人说我伙同员工飞单。这件事情当初大家已经沟通过,也澄清过。既然当时说清楚了,为什么等人走了以后,又开始把这些事情往我身上扣?如果真是我干的,把证据拿出来。聊天记录、转账记录、客户记录,有什么摆什么。别人在的时候不说,人走了以后再换一套说辞。 还有小光头这件事,我也一次讲清楚。员工做号商这件事情,当初究竟是谁知情、谁同意的,相关人员自己心里清楚。现在出了问题,却想把责任全部推到我身上?甚至关于所谓“回扣”的事情,现在也往我头上扣。那更简单了:谁拿了钱,把流水摆出来;谁收了回扣,把证据摆出来。别靠一张嘴给别人定罪。 我不怕把

5 Sept 2026, 13:52 UTC≈3,020 viewsread 6 September 2026
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#斯里兰卡资讯:又有一名中国公民因港口城谋杀案被捕 据科伦坡犯罪调查局(CCD)消息,针对此前发生的中国公民驾车遭绑架杀害并被红土石掩埋弃尸案,警方于昨日(4日)在科伦坡港口城内抓获了潜逃43天的主犯。该名嫌疑人为中国籍,被捕时戴着假发进行伪装。此前,已有四名涉案的中国籍犯罪嫌疑人被警方控制。 7月23日,隶属于埃赫利耶戈达(Eheliyagoda)警察局的卡拉达纳(Karadana)警岗办案民警,在一处位于格塔赫塔(Getahetta)方向的红毛丹果园破旧房屋内发现了一具男尸。当时尸体被红土石掩盖,办案人员还在同日于努加丹达(Nugadanda)印度教寺庙附近的路边发现了一辆可疑豪华轿车。 初步调查确认死者为一名中国公民,随后深入调查显示,死者系在科伦坡港口城内遭绑架。 案发期(7月23日),当局已在卡图纳亚克班达拉奈克国际机场抓获了两名企图潜逃出境的可疑中国籍男子;上月30日,另外两名案发后逃离科伦坡、躲藏在锡吉里耶

5 Sept 2026, 13:51 UTC10 viewsread 6 September 2026
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#群友爆料:据多方受害当事人证实: HAONR翰诺寄售回收典当店铺实际经营者夏森(Bruce),出现重大资金问题,目前人已经逃回中国。 知情人士透露:夏森以店铺典当、抵押投资为幌子,向多人吸收大额资金。大量资金并未投入店铺实际经营,而是被用于赌博挥霍。 多名客户存放店内做抵押的黄金、名表等贵重物品,遭其私自转押套取现金,造成客户财产损失。 爆雷之后,夏森对外散布虚假说辞,谎称店铺已经转让给其中一名受害人,意图将店铺房租、员工欠薪、各类客户债务全部转嫁到受害方身上。经核实,不存在任何店铺正式转让协议,该受害人并未接手店铺。 已有受害者在菲律宾CIDG提交完整刑事报案材料,相关案件正在走当地警方调查流程。 在此提醒在菲华人:请大家提高警惕,远离夏森(Bruce),不要与其开展投资、典当、资金借贷等任何形式合作,避免自身财产受损。 如果也有被此人坑害的受害者,可以互相汇合证据,共同通过法律途径维权。 —————————

5 Sept 2026, 13:01 UTC13 views0 reactionsread 6 September 2026
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#网友投稿:美国大兵去哪了?在干嘛? 这才刚到泰国第一天就能闹出这么炸裂动静,直接当场对着路打飞机🤣 ———————————————— 📣欢迎加入东南亚华人交流群 🔗 https://t.me/dnyhr0 📣西港日记/柬埔寨新闻资讯 🔗:https://t.me/xigang8I8 ✅广告招商投稿澄清爆料: @jpz8i8

5 Sept 2026, 13:00 UTC≈2,440 viewsread 6 September 2026
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国际反诈会议召开在即 彰显柬埔寨清剿电诈决心 柬埔寨将于9月23日至24日主办打击网络诈骗国际会议。柬打击网络诈骗特别委员会秘书处副秘书长泰阿斯那利表示,主办此次会议旨在向全球展示柬埔寨坚决打击跨国网络电诈、绝不妥协与退缩的政治决心。 据悉,本次会议将汇聚各国政府、执法机构、金融机构及科技公司代表,共同分享反诈经验。 柬埔寨官方强调,电诈是复杂的跨国挑战,没有任何国家能单打独斗,需通过国际合作与信息共享共同破除犯罪链条,打造安全的数字环境。^^ ———————————————— 📣欢迎加入东南亚华人交流群 🔗 https://t.me/dnyhr0 📣西港日记/柬埔寨新闻资讯 🔗:https://t.me/xigang8I8 ✅广告招商投稿澄清爆料: @jpz8i8

5 Sept 2026, 13:00 UTC≈3,850 viewsread 6 September 2026
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“美女约会”竟是全套剧本:宁波警方跨14省捣毁43个诈骗窝点 9月4日,浙江宁波警方通报一起“特殊交友”诈骗案。警方跨14个省份开展集中收网行动,捣毁诈骗窝点43个,抓获犯罪嫌疑人205名,缴获电脑126台、手机1400余部。 据警方介绍,宁波海曙区男子王某此前在刷视频时点击色情弹窗,并下载了一款交友软件。随后,软件内的“红娘”以“匹配附近女性”为由与其联系,并要求支付200多元认证费和车费。收到费用后,对方又主动退款,以此降低王某的警惕。 取得信任后,诈骗人员陆续以“二次认证”“操作失误”“账户冻结”“数据恢复”等理由,诱导王某继续转账。同时,他们还利用暧昧照片、视频和语音进行催促,诱使王某不断充值。前后,王某累计转账1.4万余元,却始终未能见到所谓的“约会对象”。 警方调查发现,该诈骗团伙分工明确、流程固定,形成了较为完整的“剧本”。团伙成员通过色情弹窗、同城交友视频和二维码等方式引流,随后以会员费、车费、酒店费、保

Showing the 12 most recent of 516 posts we hold for @feilong. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Forward network

Republishes

Channels on the register whose posts this channel has forwarded.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 5 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 5 September 2026 — this entry's latest reading, not the date you are reading this.

“菲龙网头条报道@Feilong” (@feilong), 53,647 subscribers as measured 5 September 2026. Telegram Register, tgregister.com/channel/feilong.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.