Twitter will drastically grow its user base

if it shifts its model around topics of interest

This requires a major change from an « individuals-model » relying on who to follow, to a « topics-model » designed around topics of interest.

A Timelines built around topics (not only people) will be more relevant to Twitter users. This looks like an obvious need for a platform that often feels too noisy.

Twitter users are looking for highly relevant content & topics to read and interact with, rather than spending time finding the best individuals to follow, … to then manually “filter” their content to cut the noise.
Does Twitter have the right tools to automatically discover (not to search but to discover) and to organise relevant content around verticals (verticals = topics), therefore creating a unique experience ? Probably not since, as recently recognised by Jack Dorsey, Twitter has been working hard since the beginning on helping users find individuals rather than topics and interests !

Switching from an individuals-model to a topic-model remains a major shift for a social network such as Twitter.
If some of the well-established (but not specialised) social networks are not able to adapt their strategy, they might disappear in the long run being replaced by true networks of expertise built around verticals . The topic-based use we could see in existing features such as hashtags in Twitter, is good but not enough.

Other social networks such as LinkedIn and Facebook understood the importance of verticals and have provided groups functionalities (kinds of verticals), but these functionalities might not be enough in the future in order to compete with true networks of expertise (specialised networks built around topics).

However, Twitter should be better positioned than any other social network to win in the future ! :
Twitter could become one of the leading and best networks if it operates the shift from individuals-model to topic-model in a proper way. Why ?, … because Twitter has been very successful in attracting true experts on any topic of interest, who share and interact with content of high quality.

Twitter should be seen as a treasure full of high quality content, knowledge and expertise: among the best content databases in the world, may someone find the optimal mechanism to discover, validate and filter its content !

Unfortunately, it currently does not provide the right tools to interconnect experts, communities and topics in a simple way.

Twitter’s key challenge therefore remains “How to turn noise into highly relevant signals to every single user on its platform”.

What kind of tools & solutions will help Twitter address this major challenge to eventually grow its user base ?

Some innovative startups in Twitter’s ecosystem understood the big shifts happening that already affect how we relate to and interact with online information and communities !

Indeed, some external entities to Twitter such as innovative startups, understood the power of Twitter’s networks of expertise and developed solutions around Twitter that even Twitter itself wasn’t able to offer to its users (at least up to now). Twitter should have a look at some innovative startups already playing and interacting in Twitter’s own ecosystem.
As a good example, a solution called Horizons, developed by the startup faveeo (URL: Why ? Because Horizons provides to its customers/clients what Twitter should provide to its users, for free ! 
Horizons is built around Twitter and aims at leveraging Twitter’s expertise networks to filter (through automated curation thanks to influencers behaviours) and to extract high quality content around any topic of interest. This is like a “verticalised” version of Twitter !

Horizons’s Artificial Intelligence engine couples Human Expertise and Social media analysis :
1) Human Expertise: The tool identifies and analyses Twitter experts for any topic of interest and “creates & leverages” these specialised networks to automatically validate the quality of content
2) Social media analysis to only select the most relevant content out of this subset of validated content.

This Trust-Based mechanism leveraging machine & human intelligences enables Horizons to deliver relevant content to its clients/users in the form of vertical digital magazines. Imagine if Twitter Timelines could cut the noise for you to extract relevant content only (based on your preferred topics) !

Let’s wait to see if and how Twitter will address this important challenge in the near future.