Microblog Analyses and Recommendations

Microblogs

Microblogging services have become immensely important throughout the last years as they allow users to easily share their thoughts to the public. The most successful and popular microblogging platform is Twitter, which currently serves more than 140 million active users who publish about 340 million posts each day.

Despite the huge volume of tweets posted, this data hardly features structure in terms of categorization of tweets. The only structural information available are so-called hashtags which are a means to add simple keywords as a part of the tweet. However, as hashtags may be chosen freely by the users, the hashtag vocabulary is heterogeneous. Searches for hashtags in order to find tweets concerning a certain topic may result in a search result featuring low recall due to this heterogeneity of hashtags. Our research focuses on the development of recommender systems to support users by providing recommendations for suitable hashtags. Such a recommender system aims to add structure to microblog entries and hence, a more homogeneous set of hashtags enabling better search performance.

The possibility of reaching millions of users within these networks not only attracts standard users, but also cyber-criminals who abuse the networks by spreading spam. This is accomplished by either creating fake accounts, bots, cyborgs or by hacking and compromising accounts. Compromised accounts are subsequently used to spread spam in the name of their legitimate owner. Therefore, our work sets out to investigate how Twitter users react to having their account hacked and how they deal  with compromised accounts. Further, we are highly interested in the detection of hacked accounts by analyzing the content of the user's tweets.

Team

Publications

2018

Bib Link

Bettina Larl and Eva Zangerle: Leiwand Oida: Geolocating Regional Linguistic Variation of German on Twitter. In Proceedings of the 6th Conference on Computer-Mediated Communication (CMC) and Social Media Corpora (CMC-corpora 2018). 2018

2017

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Bettina Larl and Eva Zangerle: Geolocating German on Twitter Hitches and Glitches of Building and Exploring a Twitter Corpus. In Proceedings of the 9th International Corpus Linguistics Conference (cl 2017), July 24-28, University of Birmingham, 2017

Bib Link

Benjamin Murauer, Eva Zangerle, and Günther Specht: A Peer-Based Approach on Analyzing Hacked Twitter Accounts. In Proceedings of the 50th Hawaii International Conference on System Sciences (HICSS 2017), Big Island, Hawaii, USA, January 4-7, 2017, pages 1841-1850. IEEE, 2017.

2016

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Bettina Larl and Eva Zangerle: Geolocating German on Twitter Hitches and Glitches of Building and Exploring a Twitter Corpus. In Proceedings of the 4th Conference on CMC and Social Media Corpora for the Humanities (CMC-Corpora2016), Sep. 2016, Ljubljana, Slovenia.

Bib Link

Eva Zangerle, Georg Schmidhammer and Günther Specht: Analysing the Usage of Wikipedia on Twitter: Understanding Inter-Language Links. In Proc. of 49th Hawaii International Conference on System Sciences (HICSS 2016), Kauai, Hawaii, USA, January 5-8, 2016, pages 1920-1929. IEEE, Jan. 2016.

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Eva Zangerle, Martin Illecker and Günther Specht: SentiStorm: Realtime Sentiment Detection of Tweets. In HMD Praxis der Wirtschaftsinformatik, vol. 53, no. 4, pages 514-529. Springer, 2016.

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Martin Pichl, Eva Zangerle and Günther Specht: Understanding Playlist Creation on Music Streaming Platforms. In Proceedings of the IEEE Symposium on Multimedia (ISM), pages 475-480. IEEE, 2016

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Eva Zangerle, Martin Pichl, Benedikt Hupfauf and Günther Specht: Can Microblogs Predict Music Charts? An Analysis of the Relationship Between #Nowplaying Tweets and Music Charts. In Proceedings of the 17th International Society for Music Information Retrieval Conference (ISMIR 2016), New York City, United States, August 7-11, 2016, pages 365-371.

2015

Bib Link

Martin Pichl, Eva Zangerle and Günther Specht: Towards a Context-Aware Music Recommendation Approach: What is Hidden in the Playlist Name?. In Proceedings of 15th IEEE International Conference on Data Mining Workshops (ICDM 2015), pages 1360-1365. IEEE, 2015.

Bib Link

Martin Pichl, Eva Zangerle and Günther Specht: #nowplaying on #Spotify: Leveraging Spotify Information on Twitter for Artist Recommendations. In Current Trends in Web Engineering, 15th International Conference, ICWE 2015 Workshops (Revised Selected Papers), pages 163-174. Springer, 2015.

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Eva Zangerle, Georg Schmidhammer and Günther Specht: #Wikipedia on Twitter: Analyzing Tweets About Wikipedia. In Proceedings of the 11th International Symposium on Open Collaboration, pages 14:1-14:8. ACM, Apr 2015.

2014

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Martin Pichl, Eva Zangerle and Günther Specht: Combining Spotify and Twitter Data for Generating a Recent and Public Dataset for Music Recommendation. In Proceedings of the 26nd Workshop Grundlagen von Datenbanken (GvDB 2014), Ritten, Italy, vol. 1313, pages 35-40. CEUR-WS.org, Oct. 2014.

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Eva Zangerle, Martin Pichl, Wolfgang Gassler and Günther Specht: #nowplaying Music Dataset: Extracting Listening Behavior from Twitter. In Proceedings of the 1st ACM International Workshop on Internet-Scale Multimedia Management (WISMM '14), pages 21-26. ACM, June 2014.

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Eva Zangerle and Günther Specht: “Sorry, I was hacked"—A Classification of Compromised Twitter Accounts. In Proceedings of the 29th ACM Symposium on Applied Computing (SAC 2014), pages 587-593. ACM, Mar 2014.

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Eva Zangerle and Günther Specht: Cybercrime on Twitter: Shifting the User Back into Focus. In Proceedings of the WebScience Cybercrime / Cyberwar Workshop, co-located with WebSci14. , 2014.

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Eva Zangerle: Missbrauch und Betrug auf Twitter. In Datenflut und Informationskanäle, pages 167-176, Innsbruck University Press, 2014.

2013

Bib

Eva Zangerle : Exploiting Recommendations in Microblogging Environments. In Scientific Computing@uibk. Innsbruck University Press, 2013.

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Eva Zangerle, Wolfgang Gassler and Günther Specht: On the Impact of Text Similarity Functions on Hashtag Recommendations in Microblogging Environments. In Social Network Analysis and Mining, vol. 3, no. 4, pages 889-898. Springer Vienna, 2013.

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Eva Zangerle: Leveraging Recommender Systems for the Creation and Maintenance of Structure within Collaborative Social Media Platforms. PhD thesis, University of Innsbruck, Department of Computer Science, 2013.

2012

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Eva Zangerle, Wolfgang Gassler and Günther Specht: Exploiting Twitter's Collective Knowledge for Music Recommendations. In Proceedings of the 2nd Workshop on Making Sense of Microposts (#MSM2012): Big things come in small packages, Lyon, France, 16 April 2012 (in connection with the 21st International Conference on World Wide Web), pages 14-17. 2012