diff --git a/README.md b/README.md
index 2d4a6c9..c86e499 100644
--- a/README.md
+++ b/README.md
@@ -1,2 +1,2 @@
 # BiglyCaret
-These are utilities to measure and target online communities to promote another network. The primary target is BiglyChat, but it can be used in other applications as well.
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+These are scripts to measure and target online communities to promote another network. The primary target is BiglyChat, but it can be used in other applications as well.
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diff --git a/rank.js b/rank.js
new file mode 100644
index 0000000..4f3546a
--- /dev/null
+++ b/rank.js
@@ -0,0 +1,100 @@
+// derived from https://git.dervland.net/biglyderv/new-bigly-chat/src/branch/master/docs/stats.php
+function rankCalc(result, iterations = 10) {
+    let matrixe = {}
+    let fng = {};
+    let fnc ={};
+    let frs = {};
+    let msum_old = 0;
+    let pr = {};
+    
+    for (let unn in result) {
+        matrixe[unn] = {};
+        matrixe[unn][unn] =1;
+        frs[unn] = result[unn].followers;
+        fng[unn] = result[unn].following;
+        fnc[unn] = fng[unn].length;
+        pr[unn] = 1;
+    }
+
+    for (let unn in result ) {
+        let fnu = frs[unn];
+        for (let follow of fnu) {
+            if (follow == unn) continue;
+            let dst = fnc[fnu] || 0;
+            matrixe[unn][follow] = 1 + 0.1 / (dst + 10);
+            msum_old += matrixe[unn][follow];
+        }
+        for (let unn2 in result) {
+            if (!matrixe[unn][unn2]) {
+                matrixe[unn][unn2] = 0;
+            }
+        }
+    }
+
+    
+    for (let i = 0; i < iterations; i++) {
+        let prold = structuredClone(pr);
+        let matrixf = structuredClone(matrixe);
+        let msum = 1;
+
+        for (let una in result) {
+            pr[una] = 0;
+            if (frs[una].length == 0) continue;
+
+            for (let unb in result) {
+                prb = prold[unb];
+                if (prb < 1 / 1e6 || Object.keys(fng[unb]).length == 0) {
+                    //msum += matrixe[una][unb];
+                    continue;
+                }
+                matrixe[una][unb] = 0.03;
+
+
+                for (let unc in result) {
+                    matrixe[una][unb] += matrixf[una][unc] * matrixf[unc][unb];
+                }
+
+                msum += matrixe[una][unb];
+                pr[una] += prb * matrixe[una][unb];
+
+                console.log(msum_old)
+            }
+        }
+
+
+        for (let una in result) {
+            if ((frs[una]).length == 0) continue;
+
+            for (let unb in result) {
+                matrixe[una][unb] *= msum_old / msum;
+            }
+        }
+
+        new_sum = Object.values(pr).reduce((a,b) => a+b, 0)
+
+        for (let unn in result) {
+            h = pr[unn];
+            pr[unn] /= new_sum;
+        }
+    }
+
+    return pr;
+
+}
+
+console.log(rankCalc({
+    'david': {
+        'following': [],
+        'followers': ['davis','david','bob']
+    },
+
+    'bob': {
+        'following': ['davis','david','bob'],
+        'followers': ['davis','david','bob']
+    },
+
+    'davis': {
+        'following': ['davis','david','bob'],
+        'followers': ['davis','david','bob']
+    }
+},100));
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