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I guess you meant phishing, not fishing? It would be good for you to change the title fishing -> phishing or "Someone hacking".
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Been doing a little digging with this list, and it seems the 50 merits list is a great way to find alt accounts who are abusing both merits and bounties. Here is an example of one such account that has escaped red paint: Chacoin17The said account was given a total of 150 merits ALL on February 9 for spam posts that aren't even in completely proper english. All the 150 merits came from known alt abuser accounts which have already been red painted by ThePharmacist: marcuslongtheend1949chickennadoI've found more of such accounts and i can probably post a separate thread for them but for now I'll let you guys decide if this should be red painted. Going back to the topic, this just further shows how useful merit analysis actually is. Kudos to the original poster. There was some discussion about this chain, see this thread: Large amount merit transactions https://bitcointalk.org/index.php?topic=3693207.0It would be good to see other chains you found in a separate thread. -snip-
Hi sncc, Firstly, thanks for great topic. Secondly, would you mind giving me explanation why you chose the cutoff at 40 merit points, please. Why not 20, 30, 50, or 100? It is likely a arbitrary cutoff to identify potential merit abusers. Thank you, sncc. 40 or more. Check the list again... Also, you can't send 100 merits to something at once. Only 50 per user/per month. TryNinja is right, 50 is the largest number for single transaction. I chose 40 to include the peak at 40 Merits in the figure in the OP. Of course 30 and 25 have larger peaks but the list would be too long. |
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May be you are right but i have seen many forum accounts having much posts and some of them are good quality posts and they dont having some merits on those posts thats why asking.
The merit system was introduced only a few months ago and the appropriate number and distribution of merit sources are still not clear, which is why the number of merit sources has been increasing from 35 to 80. Eventually sufficient amount of merits should spread all over the forum. |
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In my case how can i earn merit as newbies have limited knowledge on cryptocurrencies existence and concepts?
Any thoughts guys?
I was surprised that Date Registered: May 19, 2018, 09:40:25 PM and that this is your first post 1 hour after your registration, already moaning the merit system. Of course (almost) no one can make high quality posts at the beginning, so you should first try by yourself to learn crypto and the forum and then to post something which you think are helpful for people. |
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It seems we went far mathematical discussion, but the point is to have various type of merit senders as sources, making the best use of their different preferences and interests, for which merit network visualization is useful.
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I think there is another reason for awarding 50 merits to a member, and this is to pass the obligation to find meritable posts to someone else. I suspect this might be the reason that some of the 50s went to TMAN for example. TMAN is unlikely to be involved in any merit scams, but he has been active in awarding merits, and I can see that a member might want to support him in that. I have also been awarded 50 merits, and this was by a member with whom I have had no interaction, and I wonder if it ws for the same reason.
Another possibility is that someone wants to get his account painted red as revenge. This can be done from a useless high rank account that got some merit points to give by default. Whatever is the case, I hope the staff which makes the final decision keep in mind all aspects while making the final decision. Totally with your point of view, Jet Cash.
Two main factors should be taken into consideration:
1) Excessively high merit points for one thread from single user.
2) Quality of the thread.
I don't see reason to judge anyone who received more than 50 merits from someone.
There are several topics, threads which are helpful, informative and, of course, worth more than 50 merits. They are invaluable topics/ threads.
As mentioned in the OP, large amount transactions do not necessarily mean that all of them are suspicious, but some of them does seem so. This list provides candidate transactions that require a closer look of each case, and the decision should be made only after that. |
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はじめまして。エアドロップ始めて色々やった結果ここにたどり着きました。 よろしくお願いします。 ID、パスワードなど登録する毎に増えてきて管理が大変になってきました。 おススメのアプリがあったら教えていただければ嬉しいです  FranzというアプリはTwitter, telegram, discord, slackなどまとめて管理できるので便利ですね。あとはシンプルにExcelなどで管理するしかないかと思います。 Bitcointalkは5ちゃんねるやAskMonaなどとは異なりルールがありますのでまずはこちらのスレッドをご覧ください。 Bitcointalkのルール、ガイドライン、FAQ https://bitcointalk.org/index.php?topic=2966475.0 |
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The idea is good, I assume the complete list of lecturers is not fixed yet but do you have a list of core lecturers? I also noticed that all the "Student Liaison" are law students at the University of Ljubljana, why don't you have student from other field and/or University? Is this project only for law students or for University of Ljubljana?
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I found this account https://bitcointalk.org/index.php?action=profile;u=2071506 basically only posts copies of others' posts in the same thread. Posts by this account that are not copies are only "Joined Airdrop" and "Proof of authentication" type ones. Copy It is cool to understand that there are such good minds that create such projects as yours. I got acquainted with each material you presented, which has a great presentation, and I think the same good future for the project itself. Good luck you guys in Your work, I support you 100%. Cool project! I think in the world now very few such responsible people, who embody ideas into reality, but Typerium project just a dream come true!
OriginalIt is cool to understand that there are such good minds that create such projects as yours. I got acquainted with each material you presented, which has a great presentation, and I think the same good future for the project itself. Good luck you guys in Your work, I support you 100%. Cool project! I think in the world now very few such responsible people, who embody ideas into reality, but Typerium project just a dream come true!
CopyI think this is helping people be introduced into cryptos through something they are already familiar with, which is huge for the community. Typically when I talk to non-crypto people, they usually ask what do I use it for and have a hard time understanding it. However, when given use case examples, they get it. It's kind of like asking people to explain how the internet works. Most people don't know how it works but they know what they do on the internet.
Original I think this is helping people be introduced into cryptos through something they are already familiar with, which is huge for the community. Typically when I talk to non-crypto people, they usually ask what do I use it for and have a hard time understanding it. However, when given use case examples, they get it. It's kind of like asking people to explain how the internet works. Most people don't know how it works but they know what they do on the internet.
Copy well very unique concept using ordinary sms service to send / receive crypto cost of send internation sms varies from operator to operator that is something to note.. second the security part how the account is protected in case of mobile lost?
Originalwell very unique concept using ordinary sms service to send / receive crypto cost of send internation sms varies from operator to operator that is something to note.. second the security part how the account is protected in case of mobile lost?
CopyReally great project, the development team is actively working on the development of the project!
OriginalReally great project, the development team is actively working on the development of the project!
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Magnificent!
I can't imagine how you able to create something like that.
Is it possible to add time stamps per frame...
The gif movie shows how the method detects the structure, and does not reflect how actual merit networks are constructed in time. So there is no time stamp here. Can you add Philippines Local board too? I posted there often. thanks
The subcommunities are automatically identified and colored by the method and I only interpreted them as local boards or subsections. |
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Update: new transactions more than 40 Merits. |
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最近日本語板にオリジナリティの高い投稿が増えてきたように思います。技術面、税法、スクリプトの知識など、ご自分の得意分野を活かした投稿は他のユーザーにとって学ぶところが多く、勉強になり楽しく読んでいます。
私も数ヶ月前から気になっていた解析手法に取り組む時間がやっとできたので、英語板基準での質の高い投稿を書く実験もかねて最近Metaにいくつかスレッドを立てていたのですが、多くのユーザーから反響があり、theymosからも返信をもらい好評でした。オリジナリティの高い投稿であれば、日本人であっても無名のユーザーであっても、ちゃんと評価されるということだと思います。
ご自分の得意分野の切り口での記事はぜひ英語板にも投稿されるとよいと思います。日本語板の質が低いと言われなくなる日は思ったより近いかもしれませんね。
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最初から最後まで一通り読み、参考になりました。
ただ、英語ほ書込み主体ですが、一度もメリット貰っていません。
日本人で、英語のどこに書き込んだら、メリットがいただけるのか、
そのスレッドを教えていただけますでしょうか。
宜しくお願い致します。
運次第としか言えないですねー 普通のところでは書き込んでもなかなか貰えないです 一応、良い投稿ならMeritあげるよスレとかもあるので挑戦するのはありかと思います airdropwwaniさんの投稿は英語板というよりbountyスレッドへの投稿がほとんどですね。上の投稿を読んでもらえば分かりますが「客観的に見て質の高い投稿にMeritを送る」わけですから、Twitterの宣伝投稿報告などには当然Meritはもらえません。また投稿するだけでMeritがもらえるようなスレッドはルール違反ですので、そのようなスレッドはありません。よい投稿を探しているというスレッドはありますが。 英語でも日本語でも役に立つ投稿をすることが第一歩です。そのあとの段階としてzaq130さんがおっしゃっているような運の話も絡んできますが、運がよいかや有名かどうかなどは自分で解決できる分野の問題ではないので、結局は自分が有用と思う投稿をするだけだと思います。Meritのことは忘れてユーザーやフォーラムにとって有用と思う投稿を続けていれば結果は自然とついてくるものだと思います。 |
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次はDEXですか。個人的には取引所にそこまで急いで上場させずに、十分に準備が整ってから大きな取引所と交渉したほうがよいと思います。いずれにせよ、おっしゃる通りHFが解決して開発を進めることが第一ですね。特徴ある通貨なので今後の展開を見守りたいです。 |
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Before you read this I really urge you to revert the title of this thread to the original. It was much better at eye-catching, even if somewhat poetic in its approach to mathematics. But finding the right way to exaggerate is helping in creating great art (and science.)
I totally agree, that's what I had in mind when I put the original title, so I restored the title. In any case eigenvectors do form a basis of the eigenspace so it should not be a big abuse. Right maybe orthonormal basis in general vector space should be more precise here for an analogy. As you noted my point is how to find out such a basis or analogous merit senders in the entire merit network space. It would be well-defined problem if it is e.g. some general vector space in mathematics as we could basically follow the Gram-Schmidt orthogonalization process for given liner independent vectors to construct a good basis. This process is not clear for the merit network space, but at least the visualization provides an intuitive approach.
To orthonormalize you'll have to both normalize and orthogonalize. The open question is how to normalize merit transfers? This "normalized merit" would have to meet the conditions of being a https://en.wikipedia.org/wiki/Lebesgue_measure , preferably of the order 2, which is an equivalent of the most common https://en.wikipedia.org/wiki/Euclidean_distance measure, also known as https://en.wikipedia.org/wiki/Root_mean_square in statistics. In the SVD article there's a mention of open source algorithm used by Netflix to find similarities between films and user's tastes with the help of star ratings. I never had a Netflix account, but I believe the users assign films star ratings in the range 1-5 or 1-10. So they get normalization almost for free. I am not sure how the least square method works for resolving the issue, as it is not clear to me what we should minimize or fit to find out independent merit senders, but you seem to have some idea?
I was trying to make a funny reference to https://en.wikipedia.org/wiki/Ordinary_least_squares , a form of https://en.wikipedia.org/wiki/Regression_analysis . Perhaps you were trying to intuit some form of https://en.wikipedia.org/wiki/Correlation_clustering ? Please do continue your research. I have never heard about the Netflix ratings but there should be some earlier works on this kind of issue. Actually I think more important part is to define an analogous concept of orthogonality or linear independence for merit senders since if we have a well-defined orthogonal or linear independent set of merit senders, that's ok and we can use them as basis even without thinking about normalization. I think minimizing correlation or overlap of sent merit networks could be used as an analogous concept of orthogonalization. That should be a well-defined process. To compare two merit senders we can check the accounts they merited and see how many percentage of accounts are overlapping. We can then try to choose a set of merit senders whose overlap is minimized, and yet merits they sent can cover the entire forum as much as possible. We can then take into account number of posts, and allow more merit senders with overlap for dense region in the network space.
Would it be possible to see how many awards of 10 merits have been given to people with a current status of 'member', and which of the larger merit awarders are making awards that are predominantly single merits.
I haven't taken rank data from the forum so at this moment I cannot do this analysis. I think other statisticians in the forum can do this easily, and I will also think about that. |
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Good to hear your feedback and that you have been enjoying my post. Right, orthonormal basis vectors in general vector space should be more precise here for an analogy. As you noted my point is how to find out such a good basis or analogous merit senders in the entire merit network space. It would be well-defined problem if it is some general vector space in mathematics as we could basically follow the Gram-Schmidt orthogonalization process to construct a good basis for a given set of liner independent vectors, whose criterion is also well-defined. The corresponding process in the merit network is not clear to me, but at least the visualization provides an intuitive approach. I am not sure how the least square method works for resolving the issue, as it is not clear to me what we should minimize or fit to find out independent merit senders, but you seem to have some idea? |
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I was interested in taking a look of how each person's merit history is projected in the map of merit network space. The motivation was originally from curiosity, and now another motivation is to answer questions raised by theymos in the previous thread [1] from the network analysis point of view: These are very useful analyses, great job!
I am particularly interested in identifying people who should be made merit sources, or existing merit sources who should be given a higher monthly limit. When I originally created the system, I thought it'd be fairly easy to look through the stats and figure out who would make good sources, but it's been more difficult than I expected. Is there any additional data I can provide that would be useful?
Let us take a look of several people from the list of "Most generous merit senders". The following figures use the same setting as in [1] but only show merit transactions sent by each person at the center. QuestionAuthority  suchmoon  TMAN  EFS  Vod  dbshck  They are all different but we notice that EFS and dbshck are particularly different from others as they have been meriting posts in Turkish and Indonesian communities, respectively. It is important to have various kind of merit senders to cover the entire forum as much as possible. Further examples of such senders who cover different communities are: JayJuanGee (Economy)  xandry (Russian local board)  They act like eigenvectors or basis vectors in the merit network space. Here I am a little bit abusing the terminology in mathematics but the point is that they are independent and spanning the merit network space in some sense. From admin point of view, the next step is to choose a set of such vectors which can cover the entire forum in an efficient way. This is parallel to find out a good basis, e.g. orthonormal basis for some vector space in mathematics. In mathematics this problem is well-defined but it is not trivial for the merit network space. At least, the network analysis allows us an intuitive approach. To demonstrate it, if I choose a set of merit senders as QuestionAuthority
suchmoon
TMAN
EFS
Vod
dbshck
Foxpup
paxmao
DarkStar_
xandry
OgNasty
achow101
qwk
JayJuanGee
soniclord
the subnetwork they span covers the merit network space as follows:  It visualizes each person's role for coverage of the merit networks and gives the skeleton of the entire merit network shown in the first figure in [1]. In conclusion, the merit network analysis have the following advantages on this issue. 1) It visualizes each person's transactions and relative position in the entire merit network space. 2) It provides us qualitative understanding about how various communities they have merited to (or been merited from, see bonus below). 3) It clarifies the role of each person in the local communities. 4) These intuitive understandings would help admins to make a decision on how to adjust the monthly limit for each merit source, and to simulate a merit source candidate's coverage in the entire forum. There are several remarks on this analysis, which can be supplemented by other type of analysis, or are left for a future work. a) It focuses on Merit sent already, and hence highlights people who already have had and sent sufficient number of sMerits. It does not highlight people who do not have sufficient sMerit but deserve to be assigned as merit sources. b) It provides intuitive and qualitative understanding but does not quantify each sender's contributions by numbers, which should be supplemented by traditional data analysis. c) It counts the number of sMerit but does not tell what kind of posts they are actually meriting. It requires manual check, which however is also not straightforward. For example xandry's network is important to cover Russian community, but somehow most of his/her merited posts are "(Deleted/Off-limits/Ignored)" posts [2], which I cannot check. It is also difficult for any algorithm and data analysis to consider the balance between the number of high quality posts and distributed merit in each local community. More generally, since we do not have a quantitative definition of high quality posts, the issues related to the quality requires manual check, for which we can make use of the satellites in the merit network [1] and the table of large amount merit transactions [3]. Bonus: We can do the same game for the "Top-merited users". The following figures are merits sent to the top 3 merited people. theymos  satoshi  nullius  Finally, several people asked me what kind of tools I am using for these network analyses, and I presume there are more potential interests, so let me answer here. I am using igraph on python and Gephi, which are tools designed for social network analysis (SNA). There are many softwares and programming tools for SNA, see e.g. the list in Wikipedia [4], among which you may find your favorite ones.
Referemces: [1] sncc, "Merit network analysis: merit rank distribution and satellites", Bitcointalk, 3759121, May 12, (2018)[2] sncc, "Global structure of merit networks", Bitcointalk, 3650124, May 08, (2018)[3] sncc, "Merit stat & all transactions more than 40 Merits", Bitcointalk, 3046077, March 01 (2018)[4] Wikipedia, https://en.wikipedia.org/wiki/Social_network_analysis_software#Types_of_Software |
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