BotViz: Data Visualizations for Collaborations With Bots and Volunteers

Toxtli, Carlos; Flores-Saviaga, Claudia; Aguilar, Flor; Monroy, Alejandra; Flores, Juan Pablo; Herrejón, Jeerel; Chávez, Norma Elva; Dai, William; Almani, Needa; Desai, Shloka; Savage, Saiph

doi:10.1145/2818052.2869132

Cited by 4 publications

(4 citation statements)

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“…Future work is needed to analyze how these factors influence the results obtained from content creation requests online and to study the generalizability of our results for different instances of the crowd categories tested in this work. We look forward to testing the results obtained by tackling social media volunteers with more domain expertise, different content creation tasks, different sizes of social networks, and offer visualization of the task created [22].…”

Section: Limitations and Future Workmentioning

confidence: 99%

Understanding the complementary nature of paid and volunteer crowds for content creation

et al. 2020

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Crowdsourced content creation like articles or slogans can be powered by crowds of volunteers or workers from paid task markets. Volunteers often have expertise and are intrinsically motivated, but are a limited resource, and are not always reliably available. On the other hand, paid crowd workers are reliably available, can be guided to produce high-quality content, but cost money. How can these different populations of crowd workers be leveraged together to power cost-effective yet high-quality crowd-powered content-creation systems? To answer this question, we need to understand the strengths and weaknesses of each. We conducted an online study where we hired paid crowd workers and recruited volunteers from social media to complete three content creation tasks for three real-world non-profit organizations that focus on empowering women. These tasks ranged in complexity from simply generating keywords or slogans to creating a draft biographical article. Our results show that paid crowds completed work and structured content following editorial guidelines more effectively. However, volunteer crowds provide content that is more original. Based on the findings, we suggest that crowd-powered content-creation systems could gain the best of both worlds by leveraging volunteers to scaffold the direction that original content should take; while having paid crowd workers structure content and prepare it for real world use.

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Section: Limitations and Future Workmentioning

confidence: 99%

Understanding the complementary nature of paid and volunteer crowds for content creation

et al. 2020

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“…Experiments on virtual assistants have been recurrently made in the AI and Human-Robot Interaction research fields proving different opportunities to create affection [37] and engagement with users [21]; even home-assistant robots can be considered social entities [23]. Generative bots (those aimed to generate new and creative content by using NLP algorithms [44,48]) and social bots (those to interact in social networks, even with good [42,45] or bad [18] intentions) have been studied as well [12].…”

Section: Related Workmentioning

confidence: 99%

A new friend in our smartphone?

Portela

Granell-Canut

2017

Proceedings of the XVIII International Conference on Human Computer Interaction

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We present the findings of a quantitative and qualitative empirical research to understand the possibilities of engagement and affection in the use of conversational agents (chatbots). Based on an experiment with 13 participants, we explored on one hand the correlation between the user expectation, user experience and intended use and, on the other, whether users feel keen and engaged in having a personal, empathic relation with an intelligent system like chatbots. We used psychological questionnaires to semi-structured interviews for disentangle the meaning of the interaction. In particular, the personal psychological background of participants was found critical while the experience itself allowed them to imagine new possible relations with chatbots. Our results show some insights on how people understand and empathize with future interactions with conversational agents and other non-visual interfaces. CCS CONCEPTS • Human-centered computing → Natural language interfaces; Collaborative and social computing design and evaluation methods; Empirical studies in collaborative and social computing;

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“…Blind for review. Gatehouse, 2020; Waibel, 2014;Dosono, 2018;Peddie et al, 2017;Poghosyan, 2019;Angeli et al, 2018;Lustig et al, 2016;Tufekci, 2015;Koltai et al, 2014;Feinberg et al, 2019;Tachtler, 2017; Dingler et al, 2018;Toxtli et al, 2016;Steinhardt, 2016;Kriplean, 2010;Aal et al, 2016;Soden et al, 2019;Saxena et al, 2020;Kriplean et al, 2011;Llagostera, 2019a;Perez et al, 2020; Dolejšová et al,…”

Section: Acknowledgmentsunclassified

What do we study when studying politics anddemocracy?A thematic analysis of how politics and democracy aretreated in SIGCHI conference papers

Nelimarkka,

Vuorenmaa

2024

Preprint

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Human–computer interaction scholars are increasingly touching on topics relatedto politics or democracy. As these concepts are ambiguous, an examination ofconcepts’ invoked meanings aids in the self-reflection of our research efforts. Weconduct a thematic analysis of all papers with the word ‘politics’ in abstract,title or keywords (n=378) and likewise 152 papers with the word ‘democracy.’We observe that these words are increasingly being used in human-computerinteraction, both in absolute and relative terms. At the same time, we show thatresearchers invoke these words with diverse levels of analysis in mind: the earlyresearch focused on mezzo-level (i.e., small groups), but more recently the workhas begun to include macro-level analysis (i.e., society and politics as played inthe public sphere). After the increasing focus on the macro-level, we see a tran-sition towards more normative and activist research, in some areas it replacesobservational and empirical research. These differences indicate semantic differ-ences, which – in the worst case – may limit scientific progress. We bring thesedifferences visible to help in further exchanges of ideas and human–computerinteraction community to explore how it orients itself to politics and democracy.

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BotViz: Data Visualizations for Collaborations With Bots and Volunteers

Cited by 4 publications

References 2 publications

Understanding the complementary nature of paid and volunteer crowds for content creation

Understanding the complementary nature of paid and volunteer crowds for content creation

A new friend in our smartphone?

What do we study when studying politics anddemocracy?A thematic analysis of how politics and democracy aretreated in SIGCHI conference papers

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