Twitter, information sharing and the London riots?

Tonkin, Emma L.; Pfeiffer, Heather D.; Tourte, Gregory J. L.

doi:10.1002/bult.2012.1720380212

Cited by 67 publications

(46 citation statements)

References 6 publications

(6 reference statements)

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“…in tweet no. 4. Only in these four tweets we can find 'silakan' -please -written as 'silahkan', 'terhadap' -to -written as 'thdp', and 'banner' -banner -not even and Indonesian word and written as 'baner'.…”

Section: Table 1 Example Tweetsmentioning

confidence: 93%

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Topic Identification and Categorization of Public Information in Community-Based Social Media

Kusumawardani

Basri

2017

J. Phys.: Conf. Ser.

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Abstract. This paper presents a work on a semi-supervised method for topic identification and classification of short texts in the social media, and its application on tweets containing dialogues in a large community of dwellers in a city, written mostly in Indonesian. These dialogues comprise a wealth of information about the city, shared in real-time. We found that despite the high irregularity of the language used, and the scarcity of suitable linguistic resources, a meaningful identification of topics could be performed by clustering the tweets using the K-Means algorithm. The resulting clusters are found to be robust enough to be the basis of a classification. On three grouping schemes derived from the clusters, we get accuracy of 95.52%, 95.51%, and 96.7 using linear SVMs, reflecting the applicability of applying this method for generating topic identification and classification on such data.

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Section: Table 1 Example Tweetsmentioning

confidence: 93%

“…Twitter as a means for sharing information has been widely studied from a diverge point of view; for example, for sharing health-related information [1,2], its use in catastrophic disasters [3], and its roles in social unrest [4], among others. Its use as a probe of activities in an urban context has been discussed, e.g.…”

Section: Related Workmentioning

confidence: 99%

Topic Identification and Categorization of Public Information in Community-Based Social Media

Kusumawardani

Basri

2017

J. Phys.: Conf. Ser.

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“…Extensive public debate was generated about whether tools such as Facebook, Twitter and particularly BlackBerry Messenger (BBM) reinforced the riots by rapidly publicising them and even acting as an organising tool [1]. A study by Tonkin et al [22] shows that Twitter was not used to promote illegal activities, but instead acted more as news broadcasting, information sharing and community organising medium. Tweets during the riots contained information from news agencies, police and other authorities to calling for the public to help individuals, identify suspects, volunteer to clean the streets or raise funds for repairing damaged properties.…”

Section: Study Background: the Summer 2011 London Riotsmentioning

confidence: 99%

“…Tweets during the riots contained information from news agencies, police and other authorities to calling for the public to help individuals, identify suspects, volunteer to clean the streets or raise funds for repairing damaged properties. #LondonRiots and #RiotCleanup were among the most popular hashtags [22].…”

Section: Study Background: the Summer 2011 London Riotsmentioning

confidence: 99%

"5 Days in August" – How London Local Authorities Used Twitter during the 2011 Riots

Panagiotopoulos

Bigdeli

Sams

2012

Lecture Notes in Computer Science

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Abstract. This study examines effects of microblogging communications during emergency events based on the case of the summer 2011 riots in London. During five days in August 2011, parts of London and other major cities in England suffered from extensive public disorders, violence and even loss of human lives. We collected and analysed the tweets posted by the official accounts maintained by 28 London local government authorities. Those authorities used Twitter for a variety of purposes such as preventing rumours, providing official information, promoting legal actions against offenders and organising post-riot community engagement activities. The study shows how the immediacy and communicative power of microblogging can have a significant effect at the response and recovery stages of emergency events.

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“…For example, any reproduction of a tweet ("retweet") reaches an average of about 1,000 users (Kwak et al, 2010). On the other hand, news agencies, such as BBC, are constantly increasing the usage of Twitter as a reference in their daily news reports (Tonkin et al, 2012). A further characteristic of Twitter is its vibrant user community with a wide range of different personalities from all over the world.…”

Section: Introductionmentioning

confidence: 99%

The Stor-e-Motion Visualization for Topic Evolution Tracking in Text Data Streams

Weiler

Grossniklaus

Scholl

2015

Proceedings of the 6th International Conference on Information Visualization Theory and Applications

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Abstract:Nowadays, there are plenty of sources generating massive amounts of text data streams in a continuous way. For example, the increasing popularity and the active use of social networks result in voluminous and fastflowing text data streams containing a large amount of user-generated data about almost any topic around the world. However, the observation and tracking of the ongoing evolution of topics in these unevenly distributed text data streams is a challenging task for analysts, news reporters, or other users. This paper presents "Store-Motion" a shape-based visualization to track the ongoing evolution of topics' frequency (i.e., importance), sentiment (i.e., emotion), and context (i.e., story) in user-defined topic channels over continuous flowing text data streams. The visualization supports the user in keeping the overview over vast amounts of streaming data and guides the perception of the user to unexpected and interesting points or periods in the text data stream. In this work, we mainly focus on the visualization of text streams from the social microblogging service Twitter, for which we present a series of case studies (e.g., the observation of cities, movies, or natural disasters) applied on real-world data streams collected from the public timeline. However, to further evaluate our visualization, we also present a baseline case study applied on the text stream of a fantasy book series.

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Twitter, information sharing and the London riots?

Cited by 67 publications

References 6 publications

Topic Identification and Categorization of Public Information in Community-Based Social Media

Topic Identification and Categorization of Public Information in Community-Based Social Media

"5 Days in August" – How London Local Authorities Used Twitter during the 2011 Riots

The Stor-e-Motion Visualization for Topic Evolution Tracking in Text Data Streams

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