# Popularity of content leads to its duplication on Reddit

Revant Kumar, Suren Nihalani, Ashwini Khare, Prajwal Prasad

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Revant Kumar, Suren Nihalani, Ashwini Khare, Prajwal Prasad. Popularity of content leads to its duplication on Reddit. Georgia Institute of Technology, USA. 2014, pp.10. hal-04363490

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# Popularity of content leads to its duplication on Reddit

**Revant Kumar**

MS in Computer Science
Georgia Institute of Technology, USA

**Suren Nihalani**

MS in Computer Science
Georgia Institute of Technology, USA

**Ashwini Khare**

MS in Computer Science
Georgia Institute of Technology, USA

**Prajwal Prasad**

MS in Computer Science
Georgia Institute of Technology, USA

## Abstract

On social network sites like Reddit, users submit links or share textual content. The community upvotes (for) and downvotes (against) and reddit uses community sourcing as a means to order content. The contributed are scored that is number of upvotes minus downvotes. The popularity of a user is represented by his/her karma. In this project, we have tried to judge how the popularity of contents leads to its duplication on Reddit. Users can re-post the popular posts on various other subreddits in order to receive more upvotes, and thus increasing their karma. Here, we are looking users in two ways, one being the initial person broadcasting the link trying to obtain the critical mass and second one being people reposting content. The results from this project will depict how the users satisfy their Reddit Karma and the design implications of this in online communities.

## 1 Objectives

In this project, we have looked at the following interesting phenomenon:

$$ \textit{Karma in one reddit} \propto \textit{repost} $$

Thus, we have mainly focusing on to depict how the users satisfy their Reddit Karma and the design implications of this in online communities. We have correlated a post's score with its diffusion into other subreddits. We have tried to answer the questions such as – How often do links get reposted?, How many times does a user try to broadcast a link initially? We are trying to see whether there is a relationship between karma and repost frequency.

## 2 Background Study

As social networks and the user-generated content that populates them continue to grow in prevalence, size, and influence, understanding how users interact and produce this content becomes increasingly important. Insight into these community dynamics could prove valuable for measuring content trust, providing role-based group recommendations, or evaluating group stability and growth. For the related work, we have done readings of three papers, namely, Eric Gilbert's - "Widespread Under Provision on reddit", Cody Buntain's - "Identifying social roles in reddit using network structure" and Donn Morrison's - "Here, have an upvote: communication behavior and karma on Reddit".
Online communities rely on their members to do work for the good of everyone on the site. The links with the most up-votes bubble up to the main page, pointing everyone toward the best content. However, when too many people rely on others to contribute without doing so themselves results in under-provision. Gilbert observed that Reddit overlooked 52% of the most popular links the first time they were submitted [1]. This suggests that many potentially popular links get ignored, thus jeopardizing the site's core purpose of showing the best voted content.

The other two mentioned papers have tried to examine the users and the data posted by them on Reddit.com. They demonstrated that most of the popular links are overlooked in the first time, only a small number of users participate across community boundaries and the behavioral role of the user is directly linked to the distribution of karma.

In this project, we are also trying to examine the users and their activity. We are trying to demonstrate that popularity of content leads to its duplication on Reddit. In order to achieve this, we have used the Reddit API to collect the data across various subreddits at various times of the day.

Some of the questions that we have tried to answer in our project are as follows:

* How often does reposting of content happen?

* Is there a triggering score at which reposts occur?

* Which subreddits are the first places of the posting?

* Is it that less common subreddits get content first because it's easier to reach the front page?

* How often do links do well in one Reddit and in other ones?

## 3 Data Collection

We split the data collection into two phases.

During the first phase, we choose 12 subreddits to monitor. Thanks to http://redditlist.com/ we were able to look at subreddits ordered by highest subscribers. The subreddits chosen for this study were:

* /funny

* /adviceanimals

* /videos

* /music

* /technology

* /nottheonion

* /punny

* /adviceatheists

* /youtube

* /radioreddit

* /programming

* /theonion

Reddit has two types of submissions, namely links and self posts. Self posts are textual submissions. We decided to only look at links because links are binary in the sense that either link leads to the same content or it doesn't. Textual posts might have similar meaning but text might be different. For the purposes of this study, we are only looking at links.

Every minute, for 8 days, we took a snapshot of all links shared in /new and /hot queue of these subreddits. After 8 day, we wait for five days hoping that most diffusion of links has occurred by then. Our assumption here is that people will share links that they will see links only on the popular page and by five days, the popularity would have been flushed well.

Now, in the second phase, we take each of the links, and see what other subreddits it has been posted in. We store the map of link to posts in other subreddits. This comprises our data set.
<table><caption>Table 1: Data Analysis</caption><tr><td>Number of Posts</td><td>42992</td></tr><tr><td>Number of Unique Authors</td><td>33044</td></tr><tr><td>Number of links reposted at least once</td><td>7541</td></tr></table>

For the period of 8 days, we managed to get hold of about 42992 posts. Out of these posts, there were about 33044 unique authors and there were about 7541 posts with at-least one repost.

# 4 Data Analysis

The statistics of the data collected can be seen in Table1.

## 4.1 Chains

Once we have obtained all the posts, we search each of the posts on reddit in order to get their diffusion across the various sub-reddits since their inception. Thus, we think of the search results like a diffusion chain. We have sorted the results by time and we call the first person to post the link as the original author. How many times the original author posts initially is how much effort he puts into broadcasting the link. After this, we have found the search result with max score so that we can know when a particular reached its maximum popularity. All results to the left of the max post form the left chain and after wards form the right chain.

An example of chains can be seen in the following figure:

<figure><img src="image_2.png" /><figcaption>Figure 1: Description of Chain</figcaption></figure>

In this example, we have three results, the last result has the max score, so our left chain length is 2 and right chain length is 0. Note that we don't do normalization with respect to how many subscribers are in theania.

## 4.2 Distribution of Chain Length

Figure 2 shows distribution of chain length of posts i.e. distribution of how far links go. It can be observed that most chain lengths are less than 50. There is a decreasing trend in distribution. Thus, posts with longer chains are less in number. However, there is one anomaly. We notice a tiny growth at the end near the 230-240 bucket with like nothing in between. This post has 235 shares and turned out to be a spam link where every-time a randomly generated unique author posted in /r/funny.

The average chain length was found to be 1.68 with a standard deviation of 2.88.
<figure><img src="image_3.png" /><figcaption>Figure 2: Distribution of Chain Length</figcaption></figure>

4.3 Distribution of Original Author Re-posting

Figure 3 shows that distribution of posts by the original author. So, it basically shows the number of times the original author is reposting his/her own link in order to broadcast it so that it becomes more popular which eventually leads to a higher karma for him/her. We observed that the maximum number of times author has reposted has gone to 12 in our dataset.

The original author makes a submission more than once 7% of the times. When we considered only posts that had been reposted at least once, we found that in around 28.8% of the cases, the original author had made a submission more than once.

<figure><img src="image_4.png" /><figcaption>Figure 3: Distribution of Original Author Re-posting</figcaption></figure>
## 4.4 Distribution of Re-posts by each Subreddit

Figure 4 shows the distribution of posts and re-posts by each subreddit. Thus, here we are looking how much repost happens in each subreddit. We were expecting a lot of reposts from subreddits adviceanimals or funny because most of them are meme based subreddits but programming and technology came out on the top. It is interesting to note that 73% of the posts in subreddit technology were reposts.

<figure><img src="image_5.png" /><figcaption>Figure 4: Distribution of Re-posts by each Subreddit</figcaption></figure>

## 4.5 Distribution of Different Authors Re-posting

Figure 5 shows the distribution of different authors re-posting. So basically it calculates a ratio of unique authors by the chain length. If this ratio is 1, this means that all authors in post's chain are unique. We observed that that ratio is 1 in most of the cases. Thus, the chain of most of the posts on Reddit consist of unique authors i.e. most of the time it's only unique people who are reposting. We observe that around 77.36% of times, the reposts by different authors is more than those by the same author.

<figure><img src="image_6.png" /><figcaption>Figure 5: Distribution of Different Authors Re-posting</figcaption></figure>
## 4.6 Distribution of Left Chain Length

Figure 6 shows distribution of left chain length. This distribution basically shows us how people try to make a particular post happening and popular. It tells the factors that led to the post's maximum popularity in the entire chain. It is observed that left chain for most posts is less than 30. Also, a decreasing behavior is observed as expected. However, again there is an anomaly in the graph near the 225-230 bucket. We looked at it, that post has a left chain length of 229 and found that it turned out to be a spam link where every-time a randomly generated unique author posted in /r/funny. The average left chain length was found to be 0.231 with a standard deviation of 2.015.

<figure><img src="image_7.png" /><figcaption>Figure 6: Distribution of Left Chain Length</figcaption></figure>

## 4.7 Distribution of Right Chain Length

Figure 7 shows the distribution of the right chain length. It basically shows how far diffusion of a link can go. It was observed that no link made it more than 50 reposts after the point in the chain when the post was at its highest popularity. Also, a decreasing behavior was observed. The average right chain length was found to be 0.45 with a standard deviation of 1.76.

<figure><img src="image_8.png" /><figcaption>Figure 7: Distribution of Right Chain Length</figcaption></figure>
## 4.8 Distribution of Max Score by the Right Chain Length

Figure 8 shows the scatter plot of the maximum score achieved and the right chain length of each post in the data-set. So, it was observed that for most of the posts, the right chain length is less than 20 even for very high maximum scores. Also, some unexpected results were observed such that some posts with even very low maximum score had very large right chain length and some posts with very high maximum score has very small right chain length. The pearson correlation coefficient between max score and right chain length is 0.24 which suggests that there is some correlation between the two, but it is of a lower degree.

<figure><img src="image_9.png" /><figcaption>Figure 8: Distribution of Max Score by the Right Chain Length</figcaption></figure>

## 4.9 Distribution of Maximum Score of the chains

Figure 9 shows the distribution of the maximum score of the chains in our dataset. We had expected the figure to be at highest around the low scores, and have a decreasing nature with a long tail. However, we noticed a surge in posts with scores around 3000.

<figure><img src="image_10.png" /><figcaption>Figure 9: Distribution of Maximum Score of the chains</figcaption></figure>
# 5 Comparison with Eric Gilbert's Paper on Widespread Under-provision on Reddit

We compared our results with a related study done by Eric Gilbert who found that only around half of the popular links were noticed in the initial submission. Gilbert's dataset was popular links from /r/pics modsub. We found similar results when we evaluated the same figures for our dataset of 12 sub-reddits.

* Widespread Under Provision on reddit – Eric Gilbert

- Analyzed 9,370 popular links

- 48% links noticed on first submission

- Refer figure 12

<figure><img src="image_11.png" /><figcaption>Figure 10: Times a popular link has an earlier submission</figcaption></figure>

* Our Study

- Analyzed 42,992 links

- 12 subreddits

- 78.28% links noticed on first submission

- Refer figure 13

<figure><img src="image_12.png" /><figcaption>Figure 11: Times a popular link has an earlier submission</figcaption></figure>
# 6 Anomalies with the Data

## 6.1 Forbidden Links

We found some posts that reddit has banned directly on API level. An online search of the given link redirected to a 403 Forbidden Error page. Interestingly, the link has a politically sensitive article. Moreover, it is no where mentioned in their API documentation to get an error of this nature. One of such pages can be seen in the following image:

<figure><img src="image_13.png" /><figcaption>Figure 12: Link which is forbidden on Reddit</figcaption></figure>

## 6.2 Posts having chain length of 235

Post having a chain length of 235 was too good to be true. So, we checked it manually and found that it turned out to be a spam link where every-time a randomly generated unique author posted in /r/funny. It's pretty creepy to see that someone is using the API to growth hack their website. The domain name is expired. It doesn't make sense. A screenshot of that page is shown below:

<figure><img src="image_14.png" /><figcaption>Figure 13: Post with a chain length of 235</figcaption></figure>
## 6.3 Exception Handling and Issues with PRAW

We just wanted to point out the difficulties that we faced in data collection. A lot of exception handling had to be done to take care of various issues to collect a dataset with a decent number of records. We had email alerts set up to notify whenever our bot found a new error. Also, the python wrapper we used to collect data had its own issues which forced us to recollect data in Phase 2.

## 7 Conclusion and Future Work

In this project, we make a number of interesting observations and obtain some useful insights on content duplication in reddit. We observe that in some subreddits such as r/technology, around 73% of the links have already been submitted before. We find that 22% of the posts have gained more scores(upvotes-downvotes) when they have been resubmitted. Also, we find that the chain length after a post gains popularity is around twice the chain length before a post has reached its maximum score in the chain. Although the extent of correlation isn't great, we find that correlation exists between a post's top score and the post being reposted, which suggests that popularity may be a factor in the duplication of content. However, there are some limitations. Firstly, our analysis is limited to the 12 subreddits we have considered. Though we have used both popular and smaller subreddits, the representativeness of the set to be extended to reddit in general needs to be verified. Secondly, we are limited by the reddit API to obtain any information regarding a user's list of subscribed subreddits and his likes or upvotes. Thus it becomes difficult to discern if a user reposted a link after viewing it in a subOXedit, or any other source, and whether the post's score influenced him to repost the link.

One of the research questions that interests us is 'What type of users often make duplicate submissions?' Thus our future work involves studying users reposting behaviour. It would be interesting to find what % of a user's karma is obtained purely by reposted links. Also, studying a user's reposting behaviour may help us detect spam attempts similar to the one we detected in this project.

## 8 References

* Eric Gilbert. 2013. Widespread underprovision on Reddit. In Proceedings of the 2013 conference on Computer supported cooperative work (CSCW '13). ACM, New York, NY, USA, 803-808

* Cody Buntain and Jennifer Golbeck. 2014 Identifying social roles in reddit using network structure. In Proceedings of the companion publication of the 23rd international conference on World wide web companion (WWW Companion '14) International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland, 615-620

* Morrison, Donn, and Conor Hayes. 2013. Here, have an upvote: communication behaviour and karma on Reddit. GI-Jahrestagung