Social Listening User Guide

Analyze consumer perceptions from the social web using our Instant Search and Saved Search dashboards.

Seth Bridges avatar
Written by Seth Bridges
Updated over a week ago

In Rival IQ, you'll find two powerful listening tools for analyzing conversations on the social web, Instant Search and Saved Searches. Both of these tools are backed by the power of the Quid platform and bring you insights from millions of posts and documents from Twitter, Reddit, Blogs, and more.

In this article, we'll cover how to use these features along with best practices for building searches.

Finding the Dashboards

You'll find our Instant Search and Saved Searches dashboards in the Social Listening section of Rival IQ, just inside the Social Web by Quid subsection.

Data Sources

Both the Instant Search and Saved Searches dashboards analyze a collection of posts and documents from the social web using the Quid platform.

Included Sources

In these features, the data sources you can analyze include posts published in the last 30 days from the following sources:

  • Blogs: Sites like the Mommy Blog, Kotaku, Gizmodo, Gawker, or LiveJournal.

  • Blog/article comments: Comments on blogs and news articles.

  • Forums: Sites like Reddit, Parenting Forums, eBay forums, BabyCenter, Gaia Online, CafeMom, or InvisionFree.

  • News: Sites like the New York Times or PR Newswire. News sources do not include the author's name or demographics.

  • Professional reviews: Sites like CNET or PCWorld.

  • Twitter decahose: a 10% sample of the Twitter firehose (i.e., 1 in 10 Twitter posts).

  • YouTube: a sample of videos from YouTube. Results include comments on videos.

  • Other: Other selected sources around the web

Sources not included

The collection of data sources you can analyze in our social web listening tools do not include the following sources:

  • Facebook posts and comments

  • Instagram comments and hashtag tracking

  • TikTok posts and hashtag tracking

  • Twitter firehose

  • LexisNexis premium news

If you're interested in listening capabilities for any of these sources using full access to the Quid platform, please contact our team.

The Instant Search Dashboard

The Instant Search dashboard is the easiest way to get started analyzing conversations from the social web.

Option 1: Use One-Click Searches to Analyze a Brand

An easy way to start your analysis of a brand or organization in your landscape is by clicking one of the recommended brand searches on the bottom part of the dashboard.

For example, clicking on "Nordstrom" in the above example will use our AI-powered query generation system to generate keywords to search for conversations and mentions of Nordstrom across the social web.

Rival IQ will then run the analysis using the brand query and return results about your search, including key metrics, popular terms, sentiment drivers, and more.

Option 2: Start Your Search by Choosing Primary Terms to Analyze

To analyze a brand or topic that isn't in your landscape, start your search by enumerating keywords or phrases to find in our social web dataset.

Our Instant Search tool will look for documents containing ANY of the terms or phrases you include in your search.

For example, in the image below, we're setting up a search to match any document that mentions any of: Nordstrom, @nordstrom, or #nordstrom.

Press the blue Search button to start your analysis.

Rival IQ will then run the analysis using the brand query and return results about your search, including key metrics, popular terms, sentiment drivers, and more.

Editing your query

After you execute your one-click search, you can edit your query to refine the keywords, sources, domains, and authors being searched.

Click the Edit button in the upper left to access the query editor.

Read below to learn more about the Query Editor.

Using on-page filters

To help you quickly refine your analysis, we've provided three on-page filters to narrow your analysis by source, sentiment, or language.

The source and language filters enable you to reduce the selections you made in the query editor (since source and language settings are able to be defined there).

The sentiment filter enables you to narrow your analysis to positive, negative, or neutral content.

The Saved Searches Dashboard

There are a number of reasons to save a social web topic in Rival IQ. Perhaps you want to easily revisit your analysis. Perhaps you'd like to compare the volume or sentiment of multiple searches simultaneously. Perhaps you'd like to receive an alert on significant increases in conversation volume on a search.

Creating a Saved Search in Rival IQ

There are two ways to create a saved search in Rival IQ.

Option 1: Start from the Saved Searches Dashboard

One way to get started on creating a saved search is to start from the Saved Searches Dashboard.

Use the Create New Search button to start the creation process.

From there, choose the keywords, language, and sources that will define your topic. To save your search and view the results, hit the Save Search button.

Option 2: Start from an Instant Search

A second way to create a saved search is to use the Save Search button within the query editor for an Instant Search.

Option 3: Modify an Existing Search and Save as a New Search

A third option for creating a saved search is to edit an existing search and use the Duplicate Search button within the query editor. Using this path will not affect the existing saved search.

Editing an Existing Search

To edit the definition of an existing search, you can use the Edit Search button on the far right of the search row on your Saved Searches Dashboard.

Alternatively, you can edit the search query from the fast switcher in the dropdown menu located in the title bar.

Editing the Name of an Existing Search

To edit the name of an existing search, you must use the Edit Search Name button located on the far right of the search row on your Saved Searches Dashboard.

Using the Query Editor

The social web query editor is an easy-to-use way to define your listening searches in Rival IQ.

There are three primary sections in the query editor that help you define your analysis.

Choose Keywords

In this section, you'll define the words and phrases that you're looking for (and looking to avoid) in your query.

There are three main inputs. Let's take them one at a time.

FIND posts with any of these primary terms

The first input enables you to find any document in our search index that matches ANY of the words, phrases, hashtags, or social handles you specify.

In the example below, we'll find any document/post that contains the word Nordstrom, the handle @Nordstrom, or #nordstrom.

Additionally, we call these our primary terms because the words or phrases that you use in this input will be the object of our sentiment analysis for this search.

For example, consider the following sentence: "I love shopping at Nordstrom, but I hate when my children scream the whole time."

The sentiment of the first phrase is a positive mention of Nordstrom, even though the second phrase in the sentence has a negative sentiment.

INCLUDE posts with any of the following

The second input in this section allows us to refine and narrow our query to include only documents that also contain one of the specified words or phrases.

In the example below, we've used two phrases to limit our search to mentions of Nordstrom that also include mentions of San Franciso (or San Fran for short).

Just so you know, adding terms to this INCLUDE field will always narrow/shrink your results set, as it limits the results found in the initial FIND step of the search.

EXCLUDE posts with any of the following

This third input helps you further refine and narrow your query by excluding posts that match any of the words or phrases you specify.

In the example below, we're narrowing our query to remove documents/posts that mention either Gavin or @GavinNewsom.


The fourth and final input in the Choose Keywords section is the language input. You can select "All" languages to find all mentions regardless of language.

To narrow your search to documents/posts in a single language, use the dropdown to make a selection.

Choose Sources

This panel enables you to select any combination of available sources to include in your search.

Reduce Noise

In the Reduce Noise panel, there are a number of additional options to improve the relevance of your search.

First, you can use our pre-built noise filters to remove spam, ads, coupons, and more from your search.

Second, you can exclude noisy authors using the EXCLUDE authors input. Review high-volume authors using the pills below.

Finally, you can exclude noisy domains using the EXCLUDE domains input. Review high-volume domains using the pills below.

Frequently Asked Questions

For the auto-generated company searches, why do some searches also have INCLUDE Terms?

Our AI-generated queries include additional terms when we believe the brand you're analyzing might be ambiguous because its name can be confused with a common word. By including additional terms, we aim to improve the precision of your analysis. Of course, these queries are starting points that you can edit and refine further to dial in your search.

For the auto-generated company searches, why do some terms appear in both the Primary Terms and Included Terms?

For primary terms that do not need to be disambiguated from common words, like social handles or branded hashtags, we include the primary terms in the INCLUDE posts input to ensure we include all relevant results.

How is sentiment assigned to the posts? Can I change a post sentiment?

The Quid platform assigns sentiment to mentions of the primary terms using advanced natural-language processing in multiple languages.

In Rival IQ, it isn't possible to change the assigned sentiment of phrases.

What is a good Net Sentiment score?

A net sentiment score of +100 means that all opinions are positive; a score of -100 means that all opinions are negative. To analyze your brand's net sentiment in more detail, compare its net sentiment score to brands in the same category. Based on an analysis of more than 200 brands, we found that most brands have a net sentiment score of 50. Brands with the highest degree of negative sentiment have scores of 0 to slightly negative, such as -10. A score below 50 means that the net sentiment for the search is lower than most brands.

How is Net Sentiment calculated?

The net sentiment is a ratio of positive to negative opinions about your primary terms.
โ€‹( ( Positives - Negatives) / ( Positives + Negatives ) ) * 100

A single post may have multiple opinions. For example, the fictional post below has two positive opinions and one negative about ice cream:

I love ice cream. Chocolate is my favorite, but all ice cream tastes delicious. Unfortunately, I also hate ice cream because I have a dairy intolerance.

The fictional post would have a net sentiment of 33%.
โ€‹( ( 2 - 1) / ( 1 + 2 ) ) * 100 = 33.33

Why can I only see a few of the Tweets available? It says there are 30 posts from an author, but only shows 3 Tweets.

The results we compute for Twitter involve sampling and estimating due to the large volume of posts. As a result, there will be times when the available sample tweets for an author, phrases, emotion, etc., are fewer than the estimated post volume.

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