How are major social media platforms behaving in 2020?


Facebook now considers factors like loyalty in its video rankings.

As video is arguably the king of content, any change to how videos are ranked on the platform is big news.

This year, a series of algorithm updates changed how videos are ranked in the News Feed, Facebook Watch and “More Videos” recommended videos, with the aim of bringing people even more relevant, meaningful content.

Key factors affecting rankings are loyalty and intent, meaning that videos that people seek, and return to time after time, will be given more priority.

Keeping people engaged with your video is also crucial. Currently, video view time should be at least one minute to gain the favor of the News Feed algorithm. This factor will have even more weight in the future, especially in videos that are longer than three minutes.

Finally, as a part of Facebook’s efforts to reduce unoriginal and repurposed content, videos that are reposted from other channels will be demoted by the algorithm.

Experiences on the platform will now be even more personalized.

Earlier last year, a viral post started making the rounds on the internet claiming that Facebook restricts the content you see in your News Feed to 26 friends. Facebook debunked this myth themselves. What is true, however, is that the News Feed is becoming more and more personalized.

One of the bigger updates of 2019 has been the introduction of surveys in the News Feed, allowing users to indicate what kind of content they want to see more of.

The surveys ask how interested users are in seeing a specific piece of content or hearing from specific groups they’ve joined. The algorithm uses this information to predict what content and pages users are likely to care about and prioritizes this content in the News Feed. While we don’t know exactly how Facebook makes these predictions, some confirmed factors are how long the user has followed the page or group, how often they engage with content, and how actively content is posted.

Information from close friends lists, photo tags, location tags, and liking and commenting behavior are also being fed into the predictive algorithm, helping Facebook figure who you likely have a close relationship with and who you’re likely to want to hear from more.

In June 2019, personalized experiences were also rolled out to the comment section. The update changed how comments on public pages and on posts by individuals with significant followings are displayed. Comments that have a lot of engagement or engagement from the original poster will be shown first. In addition, Facebook uses surveys and signals, like engagement bait, to determine which comments to show on top.

Basically, while these updates are nothing revolutionary, they do mean that Facebook is now even better at predicting the content users want to see, and it is using even more sophisticated signals to do so.

The News Feed is now even better at recognizing spammy and biased content.

In recent years, Facebook has made strides in reducing content that is clickbait, engagement bait, or links to low-quality website experiences.

In reducing clickbait content, the purpose is to demote content that is misleading, biased or outright false. According to Facebook, the key signal they use to determine “clickbait-ness” are headlines exaggerating or withholding information. For example, a headline like “Woman loses 30 lbs with this one weird trick — you won’t believe what it is!” is a clickbait title, as it exaggerates the claim that one simple trick has lead to such a significant weight loss, and withholds key information about what the trick is.

Reducing engagement bait means demoting content that is designed to manipulate users to engage with the post. For example, a post that encourages people to share it to win a prize, or to tag their friends in the comments are engagement-baity.

For more information on both click and engagement bait and how to stay clear of it, continue reading.

In June 2019, Facebook released another update to the algorithm improving its ability to recognize and demote posts with exaggerated and misleading health claims, as well as posts that sell products advertised as “miracle cures.”


Julian Product Lead of Instagram, mentioned that there are three main factors that are the basics of the Instagram algorithm and its feed in his conference.

  1. Connections: Instagram prioritizes the posts whenever you check the Instagram feed, meaning that the first posts that Instagram shows you in the feed, are the ones that you had more interactions with them. For example, if a person comments on the posts, like them, tag you, turn the posts notification on, or DM would reach to your content more frequently.
  2. Interest: Instagram will recognize the interests of the following lists, profile visits, posts likes (from image recognitions technology), comments, and all other actions. So, using hashtags, descriptions, or any words, or category of business in bio, posts would be shown more to the users who are looking for these.
  3. Timeline: Instagram feed would show the most recent posts first, and whenever you check the Instagram feed, you’d see the latest posts. So, posting when users are online is the key.

The Instagram Algorithm Factors in Timeliness

Not only does the algorithm pay attention to how much engagement your Instagram post gets, it also how long ago the photo was posted.

Instagram’s algorithm is starting to care a lot more about when you posted, instead of just the content or engagement on the post, because it always want to serve you the latest, most interesting posts. This was brought up around the holidays last year when a lot of people were still seeing Christmas posts even though it was past New Year’s.

The Instagram Algorithm Uses Frequency to Sort Your Posts

How often do you open the Instagram app? If you’re a frequent scroller, your feed will look more “chronological” since Instagram tries to “show you the best posts since your last visit.”

If you check the Instagram app less often, then your feed will be sorted more to what Instagram thinks you’ll like, instead of chronologically.

How Does Instagram Rank Your Instagram Stories Views?

According to Julian Gutman, Product lead for Instagram Home, the people you see appearing at the top of the viewers' list is who you engage with the most, and not the other way around!

The Instagram algorithm recognizes who you are regularly interacting with and will then place them at the top of your Instagram Stories viewers list, because it knows those are the accounts you care about (or creep) the most.

How the Instagram Algorithm Works on IGTV

Right now, there’s 3 IGTV categories: For You, Following, and Popular.

  • “For You” is a collection of videos that Instagram thinks you will like, made up from people you follow and Instagram’s own machine learning.
  • “Following” is a collection of videos from all the people on Instagram that you’re already following. Which is a good time to mention that if someone follows you on IGTV, they’ll be following your regular Instagram account too!
  • “Popular” features all of the trending videos on IGTV, most likely ranked by popularity

Note: Verified users don’t get special treatment (and neither do business accounts from algorithm support perspective.)


We know from the white paper that it uses AI to track viewers’ perceived satisfaction to create an addictive, personalized stream of recommendations, i.e., it works to determine how satisfied/happy a viewer is with each video they play, and then tailor future recommendations to try and increase this level of satisfaction.

There are effectively two neural networks in use. The first filters videos to decide what would make a good match for the viewer’s “Next Up “recommendations. The second neural network gives each video a score based on a range of factors (not yet publicly known), but it appears to include an allowance for a video’s newness and the frequency of uploads on the channel that uploaded this video.

The algorithm isn’t some form of movie rater. It’s not designed to determine some scale of “goodness” for videos. It’s intended to suggest videos that the particular viewer would watch.

Ultimately, though, the system has two aims:

  1. to help viewers find the videos they want to watch
  2. to maximize long-term viewer engagement and satisfaction

The algorithm affects the six places you find video recommendations on YouTube:

  1. In search results
  2. In the recommended streams
  3. On the YouTube homepage
  4. In trending streams
  5. In channel subscriptions
  6. In notifications

YouTube Search Results

Many factors affect YouTube search results. Most of these are still unknown.

However, we know that two apparent factors have an impact:

  • How close the metadata connected to a video is to a search query term. The metadata includes things like the video’s title, description, and keywords
  • How the footage has performed to date. What types of reaction have there been to the video — likes, comments, watch times, etc.

YouTube makes it clear, though, that their algorithm confers much more than this. YouTube won’t serve you up naturally with the most-watched videos on a particular topic.

Other Factors Affecting the YouTube Algorithm

According to YouTube, there is a range of different factors that have an impact on the videos that the algorithm chooses for any individual. These include:

  • The type of content that a viewer regularly watches (and the types that he/she rarely watch). If somebody spends 95% of their YouTube time watching music videos, the algorithm will predominantly serve them other music videos
  • The length of time that people tend to watch a particular video; do most people view it to the end, or do they drop out after only a couple of seconds
  • The speed at which a video becomes popular (or not). There is probably some leeway when a video is first uploaded to give it time to gain a reputation
  • How often the uploading channel creates a new video
  • The session time that people spend on YouTube
  • Engagement — likes, shares, dislikes, numbers of comments
  • Any negative feedback


How the Tik-Tok Algorithm work

  • When a video is uploaded, TikTok shows it to a small number of TikTok users in between popular videos. This way, the user doesn’t get bored.
  • The algorithm then measures how much of your video is actually watched, as well as how many Likes, comments, shares, and downloads it receives. It seems that the ratio is 1 like for every 10 views in order to trigger the algorithm to show the video to more people.
  • The algorithm is triggered by the velocity of the engagement it receives. In other words, if it suddenly receives 20% more Likes in a single day, then the video will be pushed out to more people as a result. Users have reported that their video views seem to come in waves as a result.

Linked In

“To facilitate professional conversations in LinkedIn’s feed, we have introduced “contribution” as an additional objective in the candidate selection model. The probability of contribution captures members’ intent to share, comment, or react to a particular feed update. The model also takes into account timely feedback to content creators, which is a clear signal for cultivating and retaining audience builders on LinkedIn.”

In other words, LinkedIn has built-in an element that rewards content creators (‘audience builders’) on the platform, as opposed to merely showing users the most engaging content to maximize response.

The idea of this is to encourage more activity from across the board, and make LinkedIn, in general, a more engaging and active place of discussion. That, ideally, will keep members coming back more often — more users seeing more response equates to them posting more often, essentially re-distributing all that top-level engagement that was going to the top 1% and spreading it more evenly to foster broader participation.

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Sindhu Biswal

Sindhu Biswal

Growth Marketer @ FilterCopy, Dice Media, Gobble | Digital Media Entrepreneur | Sharing all short format marketing insights on Linked In👉