scholarly journals A Computational Analysis of Polarization on Indian and Pakistani Social Media

Author(s):  
Aman Tyagi ◽  
Anjalie Field ◽  
Priyank Lathwal ◽  
Yulia Tsvetkov ◽  
Kathleen M. Carley
Author(s):  
Nadav Hochman ◽  
Lev Manovich

How are users’ experiences of production, sharing, and interaction with the media they create mediated by the interfaces of particular social media platforms? How can we use computational analysis and visualizations of the content of visual social media (e.g., user photos, as opposed to upload dates, locations, tags and other metadata) to study social and cultural patterns? How can we visualize this media on multiple spatial and temporal scales? In this paper, we examine these questions through the analysis of the popular mobile photo–sharing application Instagram. First, we analyze the affordances provided by the Instagram interface and the ways this interface and the application’s tools structure users’ understanding and use of the “Instagram medium.” Next, we compare the visual signatures of 13 different global cities using 2.3 million Instagram photos from these cities. Finally, we use spatio–temporal visualizations of over 200,000 Instagram photos uploaded in Tel Aviv, Israel over three months to show how they can offer social, cultural and political insights about people’s activities in particular locations and time periods.


2020 ◽  
pp. 089443932091485 ◽  
Author(s):  
Deen Freelon ◽  
Michael Bossetta ◽  
Chris Wells ◽  
Josephine Lukito ◽  
Yiping Xia ◽  
...  

The recent rise of disinformation and propaganda on social media has attracted strong interest from social scientists. Research on the topic has repeatedly observed ideological asymmetries in disinformation content and reception, wherein conservatives are more likely to view, redistribute, and believe such content. However, preliminary evidence has suggested that race may also play a substantial role in determining the targeting and consumption of disinformation content. Such racial asymmetries may exist alongside, or even instead of, ideological ones. Our computational analysis of 5.2 million tweets by the Russian government-funded “troll farm” known as the Internet Research Agency sheds light on these possibilities. We find stark differences in the numbers of unique accounts and tweets originating from ostensibly liberal, conservative, and Black left-leaning individuals. But diverging from prior empirical accounts, we find racial presentation—specifically, presenting as a Black activist—to be the most effective predictor of disinformation engagement by far. Importantly, these results could only be detected once we disaggregated Black-presenting accounts from non-Black liberal accounts. In addition to its contributions to the study of ideological asymmetry in disinformation content and reception, this study also underscores the general relevance of race to disinformation studies.


2020 ◽  
Vol 42 (3) ◽  
pp. 515-538
Author(s):  
Alexis Henshaw

Abstract The idea that men and women approach conflict resolution differently forms the backbone of the international agenda on Women, Peace, and Security (WPS) and is supported by a growing body of scholarship in international relations. However, the role of women who represent insurgent groups in peace talks remains understudied, given the relatively rare appearance of such women in peace processes. The present study examines how men and women from the negotiating team of the Revolutionary Armed Forced of Colombia (FARC) engaged in public-facing discourse on Twitter leading up to a referendum on the peace accords in 2016. Using a mixed-methods approach that includes computational analysis and a close reading of social media posts, I demonstrate that women in the FARC’s negotiating team were more successful social media users than their male counterparts and that they offered a distinct contribution to the discourse on peace, centring the relevance of gender and promoting issue linkages like the need to address LGBTI rights.


2018 ◽  
pp. 111-134 ◽  
Author(s):  
Jeremy Foote ◽  
Aaron Shaw ◽  
Benjamin Mako Hill

Author(s):  
Yunhwan Kim ◽  
Donghwi Song ◽  
Yeon Ju Lee

A dramatic increase has been registered in the number of social media posts in photo form as well as in hashtag activism. Hashtags, which manifest thoughts and feelings clearly and concisely, originated on Twitter, where the length of a post is limited; their use, however, has expanded into other social media services, including Instagram. Hashtags, which make it easy to find and express support for posts of interest, have been widely used for online activism, although they have been criticized for fostering confirmation bias. Moreover, hashtag activism in photo form has been relatively understudied. This research analyzed Instagram photos with antivaccination hashtags as an example of hashtag activism through photos. In addition, we examined how the photo features were related to public response, which was manifested via engagement and comment sentiment. The results suggest that the photos which were categorized into “text” took the largest share. It was also found that the major way of claiming was to imprint key messages that persuade people not to vaccinate with remarks from professionals on photos and provide a source of supporting information in the post text with hashtags of antivaccine intention. Various photo features showed associations with engagement and comment sentiment, but the directions of correlation were usually the opposite: these results suggest that engagement and comment sentiment are separate domains that reveal different public responses.


Author(s):  
MUHAMMED ABDULLAH BÜLBÜL ◽  
SALAH HAJ ISMAIL

This study performs a data analysis on refugees in Turkey based on their social media activities. In order to achieve this, we first propose a method to find their relevant public accounts and collect their activities generating a dataset. Then, we perform spatial and temporal analysis over this dataset to shed light on the most important topics and events discussed in social networks. We present the results graphically for ease of understanding and comparison. Our results indicate that we can reveal the most shared topics over a specific time and place as well as the change of pattern in refugees’ activities through their reflection on social media. Moreover, this dataset facilitates a number of further and deeper analyses of the refugees in Turkey.


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