Linguistic Inquiry Word Count
Linguistic Inquiry Word Count - Related Videos
10:19
Using a Hemacytometer to Count Cells
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2023
Many biomedical experiments require manipulation of a known quantity of cells, in order to achieve accurate, reproducible, and statistically-relevant data. Therefore, learning how to count cells is a particularly essential technique for any successful biomedical scientist. The most common way to count cells is by using a hemacytometer - an instrument that bears two laser-etched grids, which aid in the enumeration of an aliquot cells under a simple light microscope. This data can then be used to...
05:38
Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology
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Cited by 4 •
2021
We present a protocol to explore the relative activation sequence of phonology and semantics in visual word recognition. The results show that consistent with interactive accounts, semantic and phonological representations may be processed interactively, and higher-level linguistic representations may affect early processing.
05:47
Counting and Determining the Viability of Cultured Cells
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Cited by 19 •
2008
Determining the number of cells in culture is important in standardization of culture conditions and in performing accurate quantitation experiments. In this video, we demonstrate how cells are counted using a hemacytometer.
06:37
Counting Human Neural Stem Cells
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Cited by 14 •
2007
Knowledge of the exact number of viable cells is required for many tissue culture manipulations. This protocol describes how to differentiate between live and dead cells and quantify cells using a hemacytometer. Although it describes counting human neural stem/precursor cells (hNSPCs), it can be used for other cell types.
11:25
Knowing What Counts: Unbiased Stereology in the Non-human Primate Brain
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Cited by 22 •
2009
The anatomical organization of the primate brain can provide important insights into normal and pathological conditions in humans. Unbiased stereology is a method for accurately and efficiently estimating the total neuron number (or other cell type) in a given reference space1.
FAQs
The method compares words and word stems in a text with predefined linguistic categories. A word or stem may contribute to categories representing emotion, cognition, social relationships, or biological concerns. By aggregating these matches across a sample, researchers obtain quantitative indicators of language patterns that can be examined alongside communication and behavioral measures.
Frequencies show how often category-related language appears, while proportions express that use relative to the amount of language analyzed. This distinction helps researchers characterize language patterns across written or spoken material that may differ in length. The resulting measures support standardized comparisons of emotional, cognitive, social, and biological language across research contexts.
Emotion, cognition, social relationships, and biological concerns provide distinct perspectives on language associated with behavior. Emotion-related categories can describe expressive patterns, cognition-related categories can characterize cognitive style, and social or biological categories can indicate the thematic focus of communication. Considering several categories together allows behavioral researchers to examine language from multiple psychological perspectives.
A typical workflow begins with collecting written or spoken language from a relevant context, such as an interview, online post, clinical narrative, or experiment. The text is then processed against the method’s predefined word and word-stem categories. Researchers calculate category frequencies or proportions and interpret the resulting pattern in relation to communication or behavior.
Researchers may choose this approach when they need a standardized way to examine language across interviews, online posts, clinical narratives, or experimental studies. It is useful for studying emotional expression, cognitive style, social behavior, and communication patterns. Because the same category-based procedure can be applied across materials, it supports reproducible comparisons between contexts or study groups.
The analysis provides quantitative measures of how strongly different language categories appear within a text sample. Researchers can use those measures to identify patterns in emotion, cognition, social relationships, or biological concerns, then test links between language and behavior. In this way, communication becomes a measurable source of evidence for behavioral research rather than only a qualitative description.