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Article available under the terms of the CC BY-NC-ND 2.0 licence (https://creativecommons.org/licenses/by-nc-nd/2.0/) eprints@whiterose.ac.uk https://eprints.whiterose.ac.uk/ Reuse Unless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. ABSTRACTIn this paper we investigate the role of the academic status in the following behaviour of computer scientists on Twitter. Based on a uses and gratifications perspective, we focus on the activity of a Twitter account and the reciprocity of following relationships. We propose that the account activity addresses the users' information motive only, whereas the user's academic status relates to both the information motive and community development (as in peer networking or career planning).Variables were extracted from Twitter user data. We applied a biographical approach to correctly identify the academic status (professor versus PhD student). We calculated a 2 × 2 MANOVA on the influence of the activity of the account and the academic status (on different groups of followers) to differentiate the influence of the information motive versus the motive for community development.Results suggest that for computer scientists Twitter is mainly an information network. However, we found significant effects in the sense of career planning, that is, the accounts of professors had even in the case of low activity a relatively high number of researcher followers -both PhD followers as well as professor followers. Additionally, there was also some weak evidence for community development gratifications in the sense of peer-networking of professors.Overall, we conclude that the academic use of Twitter is not only about information, but also about career planning and networking.

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Trending topics in microblogs such as Twitter are valuable resources to understand social aspects of real-world events. To enable deep analyses of such trends, semantic annotation is an effective approach; yet the problem of annotating microblog trending topics is largely unexplored by the research community. In this work, we tackle the problem of mapping trending Twitter topics to entities from Wikipedia. We propose a novel model that complements traditional text-based approaches by rewarding entities that exhibit a high temporal correlation with topics during their burst time period. By exploiting temporal information from the Wikipedia edit history and page view logs, we have improved the annotation performance by 17-28%, as compared to the competitive baselines.