Post language and user engagement in online content communities

Post language and user engagement in online content communities PurposeThis study aims to uncover relationships between content communities post language, such as parts of speech, and user engagement.Design/methodology/approachAnalyses of almost 12,000 posts from the content community Reddit are undertaken. First, posts’ titles are subjected to electronic classification and subsequent counting of main parts of speech and other language elements. Then, statistical models are built to examine the relationships between these elements and user engagement, controlling for variables identified in previous research.FindingsThe number of adjectives and nouns, adverbs, pronouns, punctuation (exclamation marks, quotation marks and ellipses), question marks, advisory words (should, shall, must and have to) and complexity indicators that appear in content community posts’ titles relate to post popularity (scores: number of favourable minus unfavourable votes) and number of comments. However, these relationships vary according to the category, for example, text-based categories (e.g. Politics and World News) vs image-based ones (e.g. Pictures).Research limitations/implicationsWhile the relationships uncovered are appealing, this research is correlational, so causality cannot be implied.Practical implicationsAmong other implications, companies may tailor their own content community post titles to match the types of language related to higher user engagement in a particular category. Companies may also provide advice to brand ambassadors on how to make better use of language to increase user engagement.Originality/valueThis paper shows that language features add explained variance to models of online engagement variables, providing significant contribution to both language and social media researchers and practitioners. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Journal of Marketing Emerald Publishing

Post language and user engagement in online content communities

European Journal of Marketing, Volume 50 (5/6): 29 – May 9, 2016

Loading next page...
 
/lp/emerald-publishing/post-language-and-user-engagement-in-online-content-communities-4ws9Xo7Flx
Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0309-0566
DOI
10.1108/EJM-12-2014-0785
Publisher site
See Article on Publisher Site

Abstract

PurposeThis study aims to uncover relationships between content communities post language, such as parts of speech, and user engagement.Design/methodology/approachAnalyses of almost 12,000 posts from the content community Reddit are undertaken. First, posts’ titles are subjected to electronic classification and subsequent counting of main parts of speech and other language elements. Then, statistical models are built to examine the relationships between these elements and user engagement, controlling for variables identified in previous research.FindingsThe number of adjectives and nouns, adverbs, pronouns, punctuation (exclamation marks, quotation marks and ellipses), question marks, advisory words (should, shall, must and have to) and complexity indicators that appear in content community posts’ titles relate to post popularity (scores: number of favourable minus unfavourable votes) and number of comments. However, these relationships vary according to the category, for example, text-based categories (e.g. Politics and World News) vs image-based ones (e.g. Pictures).Research limitations/implicationsWhile the relationships uncovered are appealing, this research is correlational, so causality cannot be implied.Practical implicationsAmong other implications, companies may tailor their own content community post titles to match the types of language related to higher user engagement in a particular category. Companies may also provide advice to brand ambassadors on how to make better use of language to increase user engagement.Originality/valueThis paper shows that language features add explained variance to models of online engagement variables, providing significant contribution to both language and social media researchers and practitioners.

Journal

European Journal of MarketingEmerald Publishing

Published: May 9, 2016

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off