Neeva Profile picture
Jan 17 11 tweets 4 min read
1/ Have you heard? Bias Buster is now available in #Neeva's main search tab!

🔎 Try a search here: neeva.com/search?q=calif…

And if you're wondering how we crawled and evaluated topics to create our 5 point scale slider, stay tuned! 🤓

We dive into it on this thread 🧵… Image
2/ Our goal? 👉 Show a variety of POVs on particular news topics.

To reach this goal, we categorized results based on 5 buckets to ensure a smooth experience while interacting with the slider. This includes:

🪣 Far Left
🪣 Left Leaning
🪣 Center
🪣 Right Leaning
🪣 Far Right
3/ So, how do we categorize our results to fit these buckets?

By using third party media bias tools, such as @AllSidesNow and @MBFC_News.

Each result is categorized by its respective domain.
4/ We use these ratings to filter and re-rank what results show in what bucket.

Categorizing domains is not a perfect science, so we make sure to show results at most one bucket away from the selection on the slider. Image
5/ With this bucketing implementation, we need to ensure that we have domains to serve from all of these perspectives.

We collected a variety of domains from each of the 5 buckets, and pulled the respective sitemaps.

These sitemaps are fed into our crawl pipeline.
6/ Previously, crawling and indexing one URL into Neeva’s own index took more than 2 weeks after the URL’s discovery.

Apparently, this is too stale in terms of serving news pages. Image
7/ In order to serve news pages in a fresh way, we build our fresh crawl-indexing pipeline.

Every hour, we crawl and index URLs from a couple of sources, including:
📌 Sitemaps
📌 Twitter feeds
📌 API crawl, etc.

From there we fast-track these pages into our Koala indexing. 🐨
8/ To utilize Bias Buster to its full potential, we implemented triggering logic.

This allows the slider to show if there are a variety of results to view on the spectrum.

We determined these queries are typically ones that have a high news intent, as well as political intent.
9/ So, we:

1️⃣ Probe the result sets pulled from the buckets to gain intuition on variety
2️⃣ Check political intent & topicality
3️⃣ Check if the query has any identified intents for which we shouldn't trigger on
10/ Here's an example...

If the query includes a site restrict, we wouldn't want to display Bias Buster, since the ultimate intent is to see results from that site. Image
11/ Overall, Bias Buster gives an opportunity for our US users to explore different perspectives on the political spectrum when available.

Head over to neeva.com to try it out and let us know what you think!

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More from @Neeva

Jan 18
1/ At #Neeva, design is the act of giving form to an idea: we gather data and inspiration, think, make, and iterate through feedback. 💡

Here's how our team, working alongside the ✨Neeva Community✨, shaped our latest news tool, #BiasBuster...

(read on 📖) Image
2/ To improve the news experience on Neeva, we solicited insights from users of various news outlets.

One early finding 👉 the journey to get daily news typically started from news providers' sites and apps, but NOT from a search engine.

🤔 Image
3/ So we asked ourselves, when does a search engine becomes necessary and helpful in the journey? 💭

Several users shared that they searched for specific events and stories about which they wanted to learn more.

An avid news user put, "Search is for focused topics.". Image
Read 13 tweets
Oct 10, 2022
1/ We redesigned our marketing home page and got 50% more clicks, and 20% more installs.

Want to learn how we did it? 🧵⬇️ Image
2/ A picture is worth 1k words 🖼

Instead of lines of text telling people why to use #Neeva, we show them!

Our new website visualizes installing Neeva so they:
🅰️ Know what to expect
🅱️ Show them the benefits of tracker blocking 🛑 and address bar search 🔎
3/ Use your words wisely ✍️

We changed our headline to be more on brand and highlight the core value people get from Neeva.

No clever wording, just real tangible benefits.
Read 6 tweets
Sep 23, 2022
1/ It's not the size, it's the skill - now releasing #Neeva's Query Embedding Model!

Our query embedding model beats @openai’s Curie which is orders of magnitude bigger and 100000x more expensive. 🤯

Keep reading to find out how... 📖
2/ Query understanding is the life blood of #searchengines. Large search engines spent millions of SWE hours building various signals like synonymy, spelling, term weighting, compounds, etc.

We don’t have that luxury. 🙄

Fortunately for us, #LLMs are here to build upon.
3/ We solve the problem of #query similarity: when 2 user queries looking for the same information on the web.

Why is this useful? Query-click data for web docs = strongest signal for search, QA, etc.; solving query equivalence => smear click signal over lots of user queries
Read 10 tweets
Jul 7, 2022
1/ Google will do just about anything to maintain its monopoly power

Fear-inducing pop-ups with misleading designs to trick users into going back to Google search ✅

What’s a competing search engine to do? The only thing we can…Design and innovate our way out of it! 🧵
2/ By default, Google Chrome comes with Google search – no surprise there.

However, if a user prefers a more privacy focused search engine, they have to jump through a few hoops to install an extension and make it as the default.

All in all not terribly difficult so far, but…
3/ The last thing Google wants is to lose a user, especially from their cash cow – search.

So, under the guise of security, upon installing a new search extension such as Neeva and attempting your first search from the omnibar, they deploy the misleading warning prompt.
Read 16 tweets
Jul 5, 2022
(1/) You know the drill. Head to a website, and get hit with a pop up asking to enable cookies.

Too often we just click “accept all” to get rid of the prompt, privacy be damned

Rather than 🤷‍♀️, we set out to get rid of these annoying banners & keeping your privacy intact.

🧵
(2/) Why should you care about cookies?

Sites save these small text files on your device and use them to track you.

Little crumbs that track sites you visit, what you shop for, and even what you search for.

That private & valuable info is sold and ads are targeted back at you.
(3/) Targeted ads make our skin crawl at Neeva, so we built Cookie Cutter to kick these invasive cookies to the curb.

So why not just block all cookies?

Unfortunately it’s not so easy, sites have to use some cookies, for example, to log you in or remember your shopping cart.
Read 14 tweets
Jun 7, 2022
1/ When someone types “neeva” into search, how do we know they mean “neeva.com” instead of “neevaneevaneeva.com”? After all, the second has 3 times as much neeva!

See how you can do much better than vanilla TF-IDF / cosine similarity for textual relevance!🧵
2/ Textual relevance is only one part of document ranking (alongside signals like centrality, page quality, and click rate)

But it’s one the most important parts and the one we’ll be covering in today’s thread.
3/ The most popular way to rank documents relative to queries is to use TF-IDF vector representation.

Essentially, this claims the more often a term occurs on a page (TF), and the less often it occurs on other pages (IDF) the more likely that term is to be relevant to the page.
Read 16 tweets

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