Хештегирование в рекламных текстах международных глянцевых журналов

Статья посвящена особенностям процесса хештегирования и функционирования хештегов в печатной рекламе. Источниками исследования послужили российские издания международных журналов за 2019-2022 гг.: "Tatler", "Elle Decoration", "Cosmopolitan", "Elle" и др. Сделан вывод, что хештеги в рекламной коммуникации международных журналов отличаются функциональной дифференцированностью и полифункциональность

A Momentum Theory for Hot Topic Life-cycle: A Case Study of Hot Hashtag Emerging in Twitter

The existing work on mining of hot topics is mainly based on topic multiplicity andattention from users in unit time. With the advent of social networking, the weight has been put on the hot topics which can effectively describe the importance and hotness of a topic. However, the researches on the influence exerted by the accumulation of attention towards hot topics and the alternation between hot topics and outdated ones are still relatively weak. In this paper, a novel algorithm for calculating the hotness of topics is proposed based on momentum. The number of the participants, but also the long tail effect of the historical accumulation on the topic is taken into consideration. Through this algorithm, we can accurately build a model for the hot topics on their emerging growing period and effectively describe the whole life circle of the topic. Additionally, the change between hot topics and old ones can be distinguished efficiently. Our experiments show that the process of a topic growing into a hot topic can be detected explicitly. Potential hot topics can be explored and the overdue ones can be rejected respectively

Language agnostic meme-filtering for hashtag-based social network analysis

Users in social networks utilize hashtags for a variety of reasons. In many cases, hashtags serve retrieval purposes by labeling the content they accompany. More often than not, hashtags are used to promote content, ideas, or conversations producing viral memes. This paper addresses a specific case of hashtag classification: meme-filtering. We argue that hashtags that are correlated with memes may hinder many valuable social media algorithms like trend detection and event identification. We propose and evaluate a set of language-agnostic features that aid the separation of these two classes: meme-hashtags and event-hashtags. The proposed approach is evaluated on two large datasets of Twitter messages written in English and German. A proof-of-concept application of the meme-filtering approach to the problem of event detection is presented. © 2015, Springer-Verlag Wien

Serious leisure in the digital world: exploring the information behaviour of fan communities

This research investigates the information behaviour of cult media fan communities on the internet, using three novel methods which have not previously been applied to this domain. Firstly, a review, analysis and synthesis of the literature related to fan information behaviour, both within the disciplines of LIS and fan studies, revealed unique aspects of fan information behaviour, particularly in regards to produsage, copyright, and creativity. The findings from this literature analysis were subsequently investigated further using the Delphi method and tag analysis. A new Delphi variant – the Serious Leisure Delphi – was developed through this research. The Delphi study found that participants expressed the greatest levels of consensus on statements on fan behaviour that were related to information behaviour and information-related issues. Tag analysis was used in a novel way, as a tool to examine information behaviour. This found that fans have developed a highly granular classification system for fanworks, and that on one particular repository a ‘curated folksonomy’ was being used with great success. Fans also use tags for a variety of reasons, including communicating with one another, and writing meta-commentary on their posts. The research found that fans have unique information behaviours related to classification, copyright, entrepreneurship, produsage, mentorship and publishing. In the words of Delphi participants – “being in fandom means being in a knowledge space,” and “fandom is a huge information hub just by existing”. From these findings a model of fan information behaviour has been developed, which could be further tested in future research

Serious Leisure In The Digital World: Exploring The Information Behaviour Of Fan Communities

This research investigates the information behaviour of cult media fan communities on the internet, using three novel methods which have not previously been applied to this domain. Firstly, a review, analysis and synthesis of the literature related to fan information behaviour, both within the disciplines of LIS and fan studies, revealed unique aspects of fan information behaviour, particularly in regards to produsage, copyright, and creativity. The findings from this literature analysis were subsequently investigated further using the Delphi method and tag analysis. A new Delphi variant – the Serious Leisure Delphi – was developed through this research. The Delphi study found that participants expressed the greatest levels of consensus on statements on fan behaviour that were related to information behaviour and information-related issues. Tag analysis was used in a novel way, as a tool to examine information behaviour. This found that fans have developed a highly granular classification system for fanworks, and that on one particular repository a ‘curated folksonomy’ was being used with great success. Fans also use tags for a variety of reasons, including communicating with one another, and writing meta-commentary on their posts. The research found that fans have unique information behaviours related to classification, copyright, entrepreneurship, produsage, mentorship and publishing. In the words of Delphi participants – “being in fandom means being in a knowledge space,” and “fandom is a huge information hub just by existing”. From these findings a model of fan information behaviour has been developed, which could be further tested in future research