Overview
The Overview tab brings together the main measurements for posts matching your query.
The Overview tab of the Social Intelligence dashboard brings post volume, sentiment, emotions, topics, and frequently mentioned terms into one view. It summarizes the posts matching your submitted query, time range, and topic filter. The other tabs expand individual measurements; Getting Started explains how to run and save a query.
A first analysis opens on Overview so that the measurements can be read together. A change in sentiment may coincide with a busy day, a particular emotion, or a different mix of topics. The summary helps identify which part of the results needs a closer look, while the dedicated tabs show how that part developed over time.
The labels describe each post as a whole. When a post matches two queries, it contributes the same sentiment and emotion labels to both results. Reading the matching posts helps establish which subject a reaction concerns.
Reading one query
With one query, Overview shows a stats bar followed by distribution charts, volume over time, and a word cloud. The same layout appears when you choose an individual query through Select, or combine several queries through Aggregate.
Stats bar
The four summary cells describe the size of the result and its most prominent classifications. The charts below show the counts and distributions behind them.
| Stat | What it measures |
|---|---|
| Total volume | The number of matching posts, displayed as hits. One author can contribute several posts. |
| Sentiment | The balance of positive and negative post counts, shown as a score and a label such as Mostly Positive. |
| Top emotion | The most frequent emotion label and its percentage of all emotion labels assigned to the matching posts, including Neutral. |
| Top topic | The most frequent topic label and its percentage of all topic labels assigned to the matching posts. |
The percentages beside Top emotion and Top topic use label counts because a post can receive several labels. Their denominators differ from the total post count shown in Total volume.
Total volume provides context for the other measurements. A score based on a few matching posts can change substantially when another post arrives. The same score across a much larger collection may change very little. The emotion and topic distributions show whether the leading label accounts for much of the result or only narrowly exceeds the next label.
Sentiment score
The Sentiment score gauge runs from -100 to +100. It subtracts the negative post count from the positive count, divides by their combined count, and multiplies by 100. Neutral posts are excluded. A score of +100 means the result contains positive posts and no negative posts; zero means the positive and negative counts are equal, or that both are zero.
The score summarizes the selected period. The Sentiment page explains the gauge's five level labels and adds charts showing whether that balance has stayed similar or changed during the period.
Sentiment distribution
The Sentiment distribution pie shows the counts and shares of positive, neutral, and negative posts across the full result. Its breakdown shows how many posts contribute to the score calculation. For example, with 30 positive, 10 negative, and 960 neutral posts, the score is +50, based on 40 of the 1,000 posts. The same score can accompany a much smaller neutral share.
The distribution also clarifies a score near zero. The result may contain mostly neutral posts, or it may contain many positive and negative posts whose counts balance out. Those are different collections to investigate, even though the gauge places both near its center. The matching posts provide the context for their labels.
Emotions volume
Emotions volume shows one bar for each emotion label. The colored segment counts posts carrying that label; the full track, including its gray remainder, represents all matching posts. Hovering over a bar shows the label's count and the total post count.
A post can appear in several bars. For example, suppose 100 posts receive 150 emotion labels in total, and 60 posts carry Joy. The Joy bar fills 60% of its track, while Joy accounts for 40% of all emotion labels. The Top emotion stat uses the second calculation.
Emotion labels add detail to the positive-negative distinction. Posts with negative sentiment may express anger, fear, or sadness, and more than one feeling can occur in the same post. The Emotions page explains the categories and how their distribution changes over time. The Emotion Classification guide provides background on the classification method.
Topics volume
Topics volume uses the same bar layout for subject categories such as News, Business, and Technology. Each bar counts posts carrying that topic label against the total number of matching posts. As with emotions, posts can belong to several topics, so the bar counts can add up to more than the post total.
The topic mix helps establish what the query has selected. A company name may appear in business reporting as well as personal accounts of using its products. An unexpected leading topic can also be a reason to inspect the feed for another meaning of the query term. Exact phrases and exclusions in Query Syntax can refine the matches when needed. The Topics page explains the categories, their distributions, and their changes over time.
Volume over time
Each bar represents an interval within the selected range. The interval is chosen automatically from the range and is either a day or a week. The chart offers three modes:
| Mode | What each bar shows |
|---|---|
| Volume | The number of matching posts in that interval. |
| Rate of change | The current interval's count minus the previous interval's count. A rise from 80 posts to 100 shows +20. Increases are green and decreases are red. |
| Cumulative | The total number of matching posts from the start of the range through that interval. |
A large Volume bar identifies when more matching posts appeared. Rate of change shows whether successive counts rose or fell, in posts rather than percent. Cumulative shows how the total built up across the range. If the last interval is still underway, its count covers only the available part of that interval.
The Volume page explains these views alongside the tab's peak, average, trend, and weekday measurements.
Word cloud
The word cloud displays frequent Hashtags, Cashtags such as $AAPL, Links grouped by site domain, and Handles mentioned in posts. Only categories with entries are offered. Larger text represents a higher count of matching posts containing that entry. Repeating a term several times within one post contributes one post to its count.
Clicking an entry adds its text to the query bar. With one query or a query chosen through Select, it updates that query. In Compare or Aggregate, it updates every query. You can review or edit the added terms in Write queries before submitting them with Analyze. The Mentions page explains the ranked tables, treemaps, and further query actions available on that tab.
Combining queries with Aggregate
Aggregate combines posts matching any active query and counts a post once even if it matches several queries. It shows the same stats bar and charts as the single-query layout, recalculated for the combined posts.
This view is useful when several queries describe parts of one subject, such as a company and its product names, or alternative phrasings of an issue. It gives the combined result while keeping those queries available separately through Select or Compare. Adding the individual query counts can double-count shared posts; Aggregate supplies the distinct-post total.
Comparing several queries
With two or more submitted queries, Compare shows their measurements together. All queries use the same time range and topic filter. Select opens the full single-query layout for a query chosen from its dropdown, so a subject can be inspected in detail without removing the others.
Comparison stats
Highest volume identifies the query with the most matching posts. Most positive identifies the query with the highest sentiment score. This is a relative ranking: if every query has a negative score, Most positive names the least negative one. The distribution chart shows the positive, negative, and neutral shares behind each score.
Top emotion shows the emotion label with the largest share within any query, together with that percentage and the query's name. Top topic does the same for topic labels. Each percentage uses the total label count within its own query, so the query named here can have fewer posts than the query with Highest volume.
Volume
The Volume chart places each query's total post count on the same scale. Query colors identify the bars and carry through to the volume time series and word cloud.
The totals matter when reading the other charts, which express each query's labels as percentages. Similar proportions can describe results of very different sizes. This chart makes that difference visible before the comparison turns to their composition.
Sentiment
The Sentiment chart opens in Score mode, with each query on the -100 to +100 scale. Switching to Distribution shows a bar split into its positive, neutral, and negative percentages. A higher score can be based on relatively few positive and negative posts, so the distribution supplies context the score alone leaves out.
Emotions
The Emotions chart gives each query a bar divided into label shares that add to 100%. These are percentages of all emotion labels assigned within that query, using the same denominator as the Top emotion stat.
The bars make differences in the emotional mix visible even when two queries have similar sentiment scores. For example, one result may have more Fear and another more Anger. Select opens the full results and feed for either query, where the posts can explain what those labels describe.
Topics
The Topics chart uses the same normalized layout for topic labels. Each segment is a share of all topic labels assigned within its query, matching the Top topic stat's calculation.
Comparing the topic mix helps explain differences elsewhere on the page. Two queries may select different kinds of discussion, such as Business coverage for one and Culture discussion for another. Their sentiment and emotion charts then summarize those different collections. The topic bars identify the difference; the matching posts show what is being discussed.
Volume over time
Volume over time stacks the queries within each interval. Its three modes describe the counts from different perspectives:
| Mode | What it shows |
|---|---|
| Volume | Each query's post count in the interval. The segment colors show which queries contributed to a busy day or week. |
| Distribution | Each query's percentage of the sum of all query counts for that interval. Changes in relative share remain visible when the overall count rises or falls. |
| Cumulative | Each query's running post total through the interval. This shows how its count accumulated across the range. |
A post matching several queries contributes to each query's segment. For example, if one query matches 100 posts, another matches 80, and 30 posts match both, the comparison totals add to 180. Aggregate counts 150 distinct posts. The stacked comparison therefore measures the query counts, which can overlap.
Word cloud
The Word cloud brings frequent entries from each query together and uses query colors to identify their source. A term can occur in more than one query's posts. Its appearance in one color does not establish that it is exclusive to that query; the cloud displays a limited selection, and the Mentions tables provide the counts for closer comparison.
Inspecting the matching posts
The Recent posts feed below the charts provides the text behind the measurements. Compare and Aggregate show posts from all active queries, with shared posts listed once. Select restricts the feed to the chosen query. Clicking a post opens its details, including a link to the original on Bluesky.
The feed's Filter by sentiment or emotion box narrows the posts already loaded by sentiment or emotion. The charts continue to summarize the full query. For the filter combinations and Show more behavior, see Getting Started.