Understanding Social Media Beyond Text: A Reliable Practice on Twitter
Social media provides high-volume and real-time data, which has been broadly used in diverse applications in sales, marketing, disaster management, health surveillance, etc. However, distinguishing between noises and reliable information can be challenging, since social media, a user-generated content system, has a great number of users who update massive information every second. The rich information is not only included in the short textual content but also embedded in the images and videos. In this paper, we introduce an effective and efficient framework for event detection with social media data. The framework integrates both textual and imagery content in the hope to fully utilize the information. The approach has been demonstrated to be more accurate than the text-only approach by removing 58 (66.7%) false-positive events. The precision of event detection is improved by 6.5%. Besides, based on our analysis, we also look into the content of these images to further explore the space of social media studies. Finally, the closely related text and image from social media offer us valuable text-image mapping, which can enable knowledge transfer between two media types.
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Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.
Posted 16 Nov, 2020
On 30 Jan, 2021
On 17 Jan, 2021
Received 22 Dec, 2020
Received 22 Dec, 2020
On 17 Nov, 2020
On 14 Nov, 2020
Invitations sent on 13 Nov, 2020
On 09 Nov, 2020
On 09 Nov, 2020
On 09 Nov, 2020
On 12 Jul, 2020
Received 11 Jul, 2020
Received 03 Jul, 2020
Received 06 May, 2020
On 06 May, 2020
On 05 May, 2020
On 04 May, 2020
Invitations sent on 01 May, 2020
On 23 Apr, 2020
On 22 Apr, 2020
On 22 Apr, 2020
On 22 Apr, 2020
Understanding Social Media Beyond Text: A Reliable Practice on Twitter
Posted 16 Nov, 2020
On 30 Jan, 2021
On 17 Jan, 2021
Received 22 Dec, 2020
Received 22 Dec, 2020
On 17 Nov, 2020
On 14 Nov, 2020
Invitations sent on 13 Nov, 2020
On 09 Nov, 2020
On 09 Nov, 2020
On 09 Nov, 2020
On 12 Jul, 2020
Received 11 Jul, 2020
Received 03 Jul, 2020
Received 06 May, 2020
On 06 May, 2020
On 05 May, 2020
On 04 May, 2020
Invitations sent on 01 May, 2020
On 23 Apr, 2020
On 22 Apr, 2020
On 22 Apr, 2020
On 22 Apr, 2020
Social media provides high-volume and real-time data, which has been broadly used in diverse applications in sales, marketing, disaster management, health surveillance, etc. However, distinguishing between noises and reliable information can be challenging, since social media, a user-generated content system, has a great number of users who update massive information every second. The rich information is not only included in the short textual content but also embedded in the images and videos. In this paper, we introduce an effective and efficient framework for event detection with social media data. The framework integrates both textual and imagery content in the hope to fully utilize the information. The approach has been demonstrated to be more accurate than the text-only approach by removing 58 (66.7%) false-positive events. The precision of event detection is improved by 6.5%. Besides, based on our analysis, we also look into the content of these images to further explore the space of social media studies. Finally, the closely related text and image from social media offer us valuable text-image mapping, which can enable knowledge transfer between two media types.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.