Source

Logical Operators

NotationDescriptionExample
term1 AND term2Returns sound bites that contain both term1 and term2.This example matches mentions containing both “coke” AND “love”:coke AND love
term1 OR term2Returns sound bites that contain either term1 or term2.This example matches mentions containing either “coke” OR “love”: coke OR love
AND NOT termOmits sound bites that contain term.The following example matches mentions of “Walmart” that do not also contain “coupon”:Walmart AND NOT coupon

Grouping Syntax

NotationDescriptionExample
(Boolean_expression)Specifies the order for processing expressions. You can add up to five levels of nested parentheses.This example directs NetBase to process the beginning OR expression first, then the ending OR expression, and finally the AND expression:(sentence:“General Motors” ORsentence:GM) AND(sentence:car ORsentence:automobile ORsentence:vehicle ORsentence:auto)
""term""Omits stemmed variants of term from the results. See https://nbq360.netbasequid.com/Enterprise/Analyst/Find_Conversations_with_Topics/Keyword_Matching/1Keyword_Matching for detailed information.The following example matches content containing the term “play,” but not any of its stemmed variants, such as “played,” “playing,” or “plays”:""play""
"phrase”Matches content containing the specified phrase. NOTE: Using double quotation marks does not suppress stemming. See https://nbq360.netbasequid.com/Enterprise/Analyst/Find_Conversations_with_Topics/Keyword_Matching/1Keyword_Matching for detailed information.The following example matches occurrences of “google” and “play” in the same sentence:sentence:google playThis example only matches occurrences of “google play” in the same sentence:sentence:“google play”

Wildcards

NotationDescriptionExample
*Matches multiple variants in the same way as structured mode (see https://nbq360.netbasequid.com/Enterprise/Analyst/Analyze_Conversations/Filtering/Using_Wildcards_in_Filters for more information):

• primary: supports preceding, embedded, and trailing wildcards, including those containing hashtags and @mentions. • sentence:, title:, paragraph:, and document: support preceding or embedded wildcards. • author: supports embedded and trailing wildcards. • hashtag: supports embedded and trailing wildcards. • mentionedAuthor: supports embedded and trailing wildcards. NOTES: • The sentence:, title:, paragraph:, and document: options do not support the wildcard formats #term* or #term*. You can, however, use these formats with the hashtag: filter. • You cannot use a wildcard in a term surrounded by quotation marks (“term”) or double double quotation marks (""term""). • You can only specify wildcards in topics that use the Decahose feed. | sentence:coke* ANDmentionedAuthor:@coke ANDhashtag:coke ANDauthor:dell ANDdomain:twitter.com |

Primary Terms

NotationTopicsThemesDescriptionDescription
primary:termYesNoDoes the following:

• Identifies term as an object to which sentiment refers (to support high precision sentiment) • Hides term by default in word clouds • Displays matches for term on the Tuner tab • Downloads Instagram posts for term if it is a hashtag | The following example specifies “coke,” “#coke,” and “@cocacola” as primary terms:primary:coke ORprimary:#coke ORprimary:@cocacola |

Scope Options

NotationDescriptionExample
term~number_of_wordsMatches mentions containing the specified terms within the specified number of words from each other. You can use the ~ operator with these scope options:title:sentence:paragraph:document:peers:NOTES:

• The maximum value for number_of_words is 30. • You cannot use the ~ operator with exact match, only with phrase match. • The ~ operator only works for terms occurring within a sentence. For example, the expression to the right would not match this sentence: “Coke = diabetes. Boycott!” | This example matches mentions where a sentence or its previous or subsequent sentences contain “coke” and “boycott” within three words:paragraph:“coke boycott”~3 | | sentence:term | (Default scope option) Returns sentences containing the specified term. | This example returns sentences containing “boycott” and “coke” in the same sentence:sentence:boycott ANDsentence:coke | | paragraph:term | Returns paragraphs (the hit sentence +/1 sentence) containing the specified term. | The following example returns paragraphs containing “blue” and “black” in the same paragraph (+/- 1 sentence):paragraph:blue ANDparagraph:black | | peersN | Returns N sentences that occur before and after the sentence matching the query. N can be a value between 1 and 10 (where peers1 is equivalent to the paragraph option). | The following example returns all mentions of Tide that also have a mention of “cleaning” within +/-4 sentences: Tide AND peers4:cleaning | | document:term | Returns documents containing the specified term. | This example returns documents containing “orange” and “white” when they appear in the same document or in a document’s titledocument:orange ANDdocument:white |

Filters

NOTES:

  • You can specify multiple values for one filter, such as mentionedAuthors:SteveJobs OR BillGates. This is the equivalent of mentionedAuthors:SteveJobs OR mentionedAuthors:BillGates.
  • NetBase enables you to combine a Boolean expression with some standard filters. This is useful for:
    • Applying filters that are not supported in Boolean, such as Include and Exclude Geographies.
    • Quickly adding items after you have defined and saved a Boolean query. For example, if define a complex query that uses many domain: filters and you later discover additional domains that you want to exclude, you can simply add them to the Exclude Domains filter instead of having to edit the Boolean expression.