When analyzing biblical text with word frequency tools, understanding stopwords becomes essential for meaningful results. Researchers who exclude stopwords in Bible analysis, filter common words from Scripture, or remove function words from biblical text discover that articles like “the,” “and,” “of” dominate raw frequency lists—obscuring the content words that carry theological meaning. The stopword exclusion option in Bible linguistics tools separates grammatically necessary but semantically less significant terms from the nouns, verbs, and adjectives that reveal biblical themes and vocabulary priorities.
Definition
Stopwords are high-frequency function words (articles, conjunctions, prepositions, pronouns) that serve grammatical purposes but carry minimal semantic content, which are filtered from text analysis to surface more meaningful content words like nouns, verbs, and adjectives that reveal themes and concepts.
What Stopwords Are NOT
- Not unimportant theologically — Words like “the,” “in,” “of” matter grammatically; exclusion is for analysis purposes, not theological dismissal.
- Not universally defined — Different tools use different stopword lists; some exclude 50 words, others 200+, based on analysis goals.
- Not always excluded — Some analyses require stopwords (grammar studies, translation comparison, stylometry); exclusion serves specific purposes.
- Not removed from the text — Stopwords are filtered from frequency counts and analysis; the original text remains unchanged.
- Not the same across languages — English stopwords differ from Greek, Hebrew, Spanish stopword lists; each language has unique function words.
- Not ignoring theological significance — Phrases like “in Christ” or “by faith” use stopwords theologically; exclusion targets individual word counts, not phrase meaning.
How Stopword Exclusion Works
Stopword filtering operates by comparing each word in the text against a predefined list of function words. When generating frequency counts, the analyzer skips any word matching the stopword list, counting only content words. Standard English stopword lists include articles (a, an, the), conjunctions (and, but, or), prepositions (in, on, of, to, from), pronouns (I, you, he, she, it, they), and common verbs (is, are, was, were, have, has, had). These words appear frequently because English grammar requires them, not because they carry thematic weight.
The distinction between function words and content words matters for semantic analysis. Function words provide grammatical structure: “the Lord said to Moses” uses three stopwords (the, to) and two content words (Lord, said, Moses). Frequency analysis with stopwords shows “the” dominating; without stopwords, “Lord,” “said,” and “Moses” surface as significant. This reveals who speaks and to whom—more useful for thematic study than knowing “the” appears 64,000 times in the KJV.
Stopword lists vary by tool and purpose. Minimal lists exclude only 30-50 most common words (the, and, of, to, in). Comprehensive lists exclude 150-200+ terms, including auxiliary verbs (can, could, should, would), possessives (his, her, their, my, your), and demonstratives (this, that, these, those). Some tools offer customizable lists, letting users add domain-specific stopwords or preserve certain function words for specialized analysis.
The toggle between including and excluding stopwords transforms analysis results dramatically. With stopwords, the top 20 words in most English Bibles are: the (60,000+), and (50,000+), of (35,000+), to (13,000+), that (12,000+), in (12,000+), he (10,000+), shall (9,000+), unto (9,000 in KJV), for (8,000+), I (8,000+), his (8,000+), a (7,000+), they (7,000+), be (6,000+), is (6,000+), it (5,000+), you (5,000+), not (5,000+), with (5,000+). Without stopwords, the top 20 become: Lord (7,800), God (4,400), said (3,900), king (2,500), people (2,000), man (2,700), children (1,600), came (1,800), Israel (2,500), made (1,500), Moses (850), David (1,000), land (1,700), day (2,000), house (2,000), great (1,500), father (1,500), son (1,800), went (1,400), hand (1,600)—revealing biblical content.
Try It on Acts1Family
Our Bible Word Analyzer includes a prominent “Exclude Stopwords” toggle that instantly transforms your frequency analysis. Try it with and without stopwords on any of 50+ English translations to see how filtering function words surfaces the theological vocabulary that matters most for Bible study and research.
Examples
Example 1: Simple Before/After Comparison (Psalms)
A homeschool teacher analyzing Psalms vocabulary with students runs frequency analysis twice—once with stopwords, once without. With stopwords, the top 10 are: the (5,900), of (3,400), and (2,700), I (1,800), my (1,200), to (1,100), in (1,000), me (900), for (800), thy (750). Students see that common words dominate but learn little about Psalms’ content. Excluding stopwords reveals: Lord (700), God (400), praise (150), soul (140), mercy (120), heart (110), righteousness (100), salvation (80), people (75), king (70)—instantly showing Psalms’ focus on praising the Lord, the soul’s relationship with God, and themes of mercy and salvation. The visual contrast teaches data analysis principles while deepening Scripture understanding.
Example 2: Intermediate Thematic Analysis (Paul’s Letters)
A seminary student studying Paul’s theology compares word frequencies across Romans, Galatians, and Ephesians with stopwords excluded. Romans emphasizes: law (78), faith (40), sin (48), righteousness (36), grace (24). Galatians shows: law (32), faith (22), Spirit (18), flesh (18), liberty (13). Ephesians highlights: church (9), grace (12), love (19), Spirit (16), unity (4). The shift from law-focused (Romans, Galatians) to ecclesiology-focused (Ephesians) vocabulary becomes quantitatively clear. Without stopword exclusion, function words would obscure these thematic distinctions, making comparative analysis difficult.
Example 3: Translation Philosophy via Stopword Patterns (KJV vs. NLT)
A linguist researching translation readability compares stopword usage in KJV and NLT. Even after excluding stopwords, KJV’s remaining vocabulary includes archaic function words like “unto,” “thou,” “thy,” “thee,” “ye”—words modern readers consider stopwords but KJV stopword lists often miss. NLT eliminates these entirely, using contemporary “to,” “you,” “your.” The researcher creates a custom stopword list including archaic pronouns and finds KJV’s vocabulary diversity drops significantly—revealing that much of KJV’s perceived lexical richness comes from grammatical variation (thou/thee/thy/thine), not semantic diversity. This quantifies intuitions about translation accessibility with data.
Frequently Asked Questions
Should I always exclude stopwords when analyzing the Bible?
Not always. Exclude stopwords for thematic and vocabulary studies where content words matter most. Include stopwords for grammar analysis, stylometry (author attribution), or when studying function word usage (e.g., preposition choices in spatial theology). The toggle serves different analytical purposes.
Why do some Bible words like “Lord” appear in stopword lists?
Quality Bible-focused stopword lists should NOT include “Lord,” “God,” “Christ,” etc. Generic English stopword lists sometimes mistakenly include semantically important biblical terms. Check your tool’s stopword list and customize if possible to preserve theologically significant vocabulary.
How many stopwords should a Bible analysis tool exclude?
Standard lists exclude 100-150 English function words. Minimal lists (50 words) preserve more data but less filtering. Comprehensive lists (200+ words) aggressive filter but risk excluding meaningful terms. Moderate 100-150 word lists balance filtering function words while preserving content vocabulary.
Can I customize stopword lists for specialized analysis?
Advanced tools allow custom lists. For Old Testament analysis, you might add frequent proper nouns (Israel, Jerusalem, Judah) if studying vocabulary beyond geography. For theological word studies, preserve all nouns/verbs but exclude only pure function words. Customization adapts analysis to research questions.
Do stopwords affect concordance results?
No. Concordances display every occurrence regardless of stopword status. Stopword exclusion affects only frequency rankings and statistical summaries. You can still search for “the,” “and,” etc., in concordances—they just won’t dominate frequency lists when excluded.
Why does “said” sometimes get excluded as a stopword?
“Said” occupies ambiguous territory. It’s a high-frequency verb (3,900+ times in KJV) that introduces dialogue structurally, functioning almost like punctuation. Some lists exclude it as a discourse marker; others preserve it as a content verb showing speech prominence in biblical narrative. This reflects definitional debates about stopwords.
How do stopwords work in Greek or Hebrew analysis?
Greek stopwords include articles (ὁ, ἡ, τό), conjunctions (καί, δέ), prepositions (ἐν, εἰς, ἐκ). Hebrew stopwords include definite article (ה), conjunction (ו), prepositions (ב, כ, ל). Each language has distinct function words. Cross-language analysis requires language-specific stopword lists matching grammatical structures of each language.
Do stopwords affect AI-generated linguistic insights?
Yes, indirectly. When AI analyzes frequency data with stopwords included, it may highlight grammatical patterns (“many uses of ‘the’”) rather than themes. Excluding stopwords focuses AI attention on semantic content, generating insights about biblical themes, character prominence, and theological vocabulary rather than grammatical trivia.
Can stopword exclusion reveal translation differences?
Yes. Dynamic equivalence translations (NIV, NLT) often use simpler stopwords (short words, common prepositions) for readability. Formal equivalence (ESV, NASB) may preserve more complex function words mirroring Greek/Hebrew grammar. Comparing stopword patterns quantifies translation philosophy differences in grammatical structure choices.
Should I exclude stopwords when exporting Bible data?
Depends on use case. For visualization (word clouds, frequency charts), exclude stopwords to highlight meaningful terms. For machine learning or natural language processing, include stopwords—algorithms need complete text. For human reading and study, excluding stopwords produces more interpretable summaries.