How Content Acquisition Method Affects Word of Mouth
Bibliographic Data
| ID | 2967720 |
|---|---|
| Authors | Zoey Chen (0000-0001-8020-0704), Jonah Berger (0000-0002-2669-8211) |
| Year | 2016 |
| Volume | 43 |
| Issue | 1 |
| Pages | 86-102 |
| Publication date | 2016-06-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Consumer Research (JOURNAL) |
| Journal identifiers | ISSN: 0093-5301 • E-ISSN: 1537-5277 |
| Publisher | Oxford University Press (PUBLISHER • GB) |
| DOI | 10.1093/jcr/ucw001 |
| OpenAlex | W2332665118 |
| Language | EN |
| Citations received | 6 |
| References cited | 79 |
People often share word of mouth with others, and such social sharing is an integral part of everyday life. But the content (e.g., stories, news, information) that people transmit can be acquired in different ways. Sometimes people find content themselves, and other times people receive content from others (e.g., via email or conversation). Might these different acquisition methods impact subsequent sharing, and if so, how? Six studies demonstrate that acquisition method can impact transmission through changing how content is processed. Compared to received content, people are more likely to associate found content with themselves, which decreases processing. Reduced processing, in turn, lowers sensitivity to diagnostic content characteristics (e.g., whether content is interesting or well written), which reduces these characteristics’ impact on sharing. Thus while receivers are more likely to share interesting (than boring) content, the difference is attenuated (and in some cases, disappeared) among finders. These findings deepen insights into the psychological drivers of word of mouth and shed light on how contextual factors, content characteristics, and the self interact to drive social transmission.
Advertising · Business · Content (measure theory) · Content analysis · Conversation · Everyday life · Linguistics · Sociology · Word (group theory) · Word of mouth · Communication · Computer Science · Digital Communication and Language · Digital Marketing and Social Media · Mathematics · Misinformation and Its Impacts · Psychology · Social Psychology
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| Unique citing works | 6 |
|---|---|
| Citations per year | 0,6 |
| Citation span | 2016 - 2026 (11) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 6 |