diff --git a/src/scala/com/twitter/graph/batch/job/tweepcred/README b/src/scala/com/twitter/graph/batch/job/tweepcred/README
index 75a2e5e49..271991de3 100644
--- a/src/scala/com/twitter/graph/batch/job/tweepcred/README
+++ b/src/scala/com/twitter/graph/batch/job/tweepcred/README
@@ -10,7 +10,7 @@ The implementation of the PageRank algorithm in Tweepcred is based on the Hadoop
 
 The preparation stage involves constructing the graph of Twitter users and their interactions, and initializing each user's PageRank score to a default value. This stage is implemented in the PreparePageRankData class.
 
-The iteration stage involves repeatedly calculating and updating the PageRank scores of each user until convergence is reached. This stage is implemented in the UpdatePageRank class, which is run multiple times until the algorithm converges.
+The iteration stage involves repeatedly calculating and updating the PageRank scores of each user until convergence is reached. This stage is implemented in the WeightedPageRank class, which is run multiple times until the algorithm converges.
 
 The Tweepcred PageRank implementation also includes a number of optimizations to improve performance and reduce memory usage. These optimizations include block compression, lazy loading, and in-memory caching.
 
@@ -70,4 +70,4 @@ The algorithm tests for convergence by calculating the total difference between
 
 This is a helper class called Reputation that contains methods for calculating a user's reputation score. The first method called scaledReputation takes a Double parameter raw which represents the user's page rank, and returns a Byte value that represents the user's reputation on a scale of 0 to 100. This method uses a formula that involves converting the logarithm of the page rank to a number between 0 and 100.
 
-The second method called adjustReputationsPostCalculation takes three parameters: mass (a Double value representing the user's page rank), numFollowers (an Int value representing the number of followers a user has), and numFollowings (an Int value representing the number of users a user is following). This method reduces the page rank of users who have a low number of followers but a high number of followings. It calculates a division factor based on the ratio of followings to followers, and reduces the user's page rank by dividing it by this factor. The method returns the adjusted page rank.
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+The second method called adjustReputationsPostCalculation takes three parameters: mass (a Double value representing the user's page rank), numFollowers (an Int value representing the number of followers a user has), and numFollowings (an Int value representing the number of users a user is following). This method reduces the page rank of users who have a low number of followers but a high number of followings. It calculates a division factor based on the ratio of followings to followers, and reduces the user's page rank by dividing it by this factor. The method returns the adjusted page rank.