diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala
index b0e991d2f2344..0a3f21ecee0dc 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/LDAModel.scala
@@ -130,7 +130,7 @@ abstract class LDAModel private[clustering] {
 
   /* TODO
    * Compute the estimated topic distribution for each document.
-   * This is often called “theta” in the literature.
+   * This is often called 'theta' in the literature.
    *
    * @param documents  RDD of documents, which are term (word) count vectors paired with IDs.
    *                   The term count vectors are "bags of words" with a fixed-size vocabulary