Member Avatar for Kann

Are there any filters that help choose the social media topics that are gonna be shared more? I was thinking about joining a course like one of these http://sites.bu.edu/social-media-analysis/ and , cause there are no clear cut rules for the viral content.
The only info (the newest) is a scheme of social media engagement by Tiffany Usher shared on Buzzsumo and then on social business section. Tiffany mentioned that only 6% of people actually read the whole text. And the title of the content gets to more than 92% of the audience (research dated 12.12.2017).

  • 3 Contributors
  • 2 Replies
  • 399 Views
  • 2 Weeks Discussion Span
  • Latest Post Latest Post by Didier_1

Dani AI

Generated

Short answer: pragmatic filters help prioritize topics that have a higher chance of being shared, but there’s no reliable “viral” formula. The useful approach is a repeatable, low-friction scoring system that converts intuition into testable bets and pairs learning with owned-distribution (email, community) so performance isn’t wholly at the mercy of platform algorithms.

A compact topic-selection filter (score 0–3 each; publish-recommendation threshold ≈ 15/24):

  • Audience fit — addresses a clearly defined segment and a real need.
  • Outcome clarity — delivers an obvious benefit or actionable takeaway.
  • Share trigger — social value (helps others, surprises, sparks debate).
  • Format fit — maps cleanly to the platform’s best format (short video, thread, carousel).
  • Discoverability — has keyword/hashtag or trending angle that aids reach.
  • Uniqueness/authority — original data, clear POV, or proprietary example.
  • Promotion path — a feasible amplification route (owned list, partners, small paid boost).
  • Measurability — success can be measured quickly (48–72 hours) with a clear KPI.

Scoring: 0 = none, 1 = weak, 2 = good, 3 = excellent. Topics scoring above the threshold become candidates for focused tests; 18+ are strong contenders for a small paid push and multi-format repurposing.

Context tied to the thread: ’s interest in training is valid — courses teach useful frameworks, but practice and the filter above make learning actionable. ’s point about algorithmic control reinforces the need to build owned channels so earned reach isn’t the only path. ’s suggestion to study high-engagement pages is most powerful when those patterns are translated into repeatable criteria (format + emotion + uniqueness) and fed into the scoring process.

A practical workflow: generate a short idea backlog, score ten candidates, pick the top two, create two headline/format variations each, test organically for ~72 hours, compare CTR/engagement/shares-per-impression, and amplify winners. Prioritize steady, measurable wins over chasing unpredictable virality.

Recommended Answers

All 2 Replies

Member Avatar for rproffitt

I hit your link and the title is "Go From Big Data to Data Scientist in Just Three Days at Boston University" which is either an bad advert of the subject of your web page. I immediately closed it and thought, I wonder what Kann was thinking when they made this page?

As to viral content, the same old system and people are in charge. Let's consider Facebook which has engaged in social engineering experiments. You are their pawn. You are being fed what they want.

More at https://techcrunch.com/2017/09/30/thinking-about-the-social-cost-of-technology/?ncid=rss&utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+Techcrunch+%28TechCrunch%29

Member Avatar for Didier_1

You need to research deeply your brand and product, after that, you should read more telling stories, start-up stories, follow fanpage (social) with the most likes and interactions to find out the interesting contents. I know a site named Quora, may you find good topics in there :)

Be a part of the DaniWeb community

We're a friendly, industry-focused community of developers, IT pros, digital marketers, and technology enthusiasts meeting, networking, learning, and sharing knowledge.