2018
DOI: 10.1007/978-3-319-92279-9_26
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Analyzing Elderly Behavior in Social Media Through Language Use

Abstract: Increasingly more elderly make use of social media in the Netherlands, being at the forefront compared to other European countries. We analyze the language use of Dutch (older) adults in Twitter in order to get insights in their behavior. Previous studies have identified several linguistic features that change as life progresses including pronouns. We don't find this change and we claim that this might be due to the fact that the users tend to adapt to the language of the platform. This is not the case for the… Show more

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Cited by 6 publications
(6 citation statements)
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“…In [15], we have shown that a behavioral analysis of the Dutch elderly based on Twitter data, can be useful to assess their attitude and interests and can have a potential positive impact on urban sustainability and healthy ageing. The analysis of hashtag use reveals that while the younger age groups have an interest in nature and sustainability, this doesn't seem to be the case for the seniors that exhibit, however an interest in locations.…”
Section: Discussionmentioning
confidence: 99%
“…In [15], we have shown that a behavioral analysis of the Dutch elderly based on Twitter data, can be useful to assess their attitude and interests and can have a potential positive impact on urban sustainability and healthy ageing. The analysis of hashtag use reveals that while the younger age groups have an interest in nature and sustainability, this doesn't seem to be the case for the seniors that exhibit, however an interest in locations.…”
Section: Discussionmentioning
confidence: 99%
“…The Twitter analysis of the creative migrants has focused on hashtags since they are a relevant source of information employed to index keywords or topics that are of interest to the user (Monachesi & de Leeuw, 2018;Pandya, Mourad, Monachesi, Kostakos, & Loven, 2018). (Hash-)tags are added by users to their tweets, they are a way to add metadata to shared content and highlight the debate that is being carried out in the platform: people are thus able to follow topics that interest them in an easy way (Bruns & Burgess, 2011;Golder & Huberman, 2006).…”
Section: Content Analysis Of Creative Migrants' Datamentioning
confidence: 99%
“…The majority of the teens' (13)(14)(15)(16)(17)(18)(19) hashtags concern mood/emotion and follow/like. Monachesi and Leeuw [1] concluded that hashtags are an important feature to discriminate age since older adults above 67 use mainly hashtags related to politics and leisure in Twitter while people below 55, use mainly hashtags in the context of work related activities and technology.…”
Section: Related Workmentioning
confidence: 99%
“…their number has been included in [4]), their content has not been considered. We contend that hashtags and URLs in tweets are indicative of users' age since they reflect users' interests and activities [1]. We propose a novel method to derive relevant features from hashtags and URLs and incorporate these into our CNN-based classification model.…”
Section: Introductionmentioning
confidence: 99%