Massimo Airoldi
Impact in
- Communication top 5%
- Social Media and Politics
- Music top 5%
- Music History and Culture
Papers in
-
- Ethics and Social Impacts of AI 8
- Music 4
- Music History and Culture 4
- Co-authors
- Davide Beraldo (1 shared paper)Alessandro Gandini (2 shared papers)Joonas Rokka (2 shared papers)Mauro Barisione (1 shared paper)Asimina Michailidou (1 shared paper)Adam Arvidsson (1 shared paper)Alessandro Caliandro (3 shared papers)Lotta K. Harju (1 shared paper)
- Journals
- Poetics (3 papers)Consumption Markets & Culture (2 papers)Information Communication & Society (2 papers)Journal of Macromarketing (1 paper)Big Data & Society (1 paper)
- Partner nations
- ItalyFranceUnited Kingdom
In The Last Decade
Massimo Airoldi
18 papers receiving 426 citations
Peers
Comparison fields: 5 of 66
- Communication 96
- Music 43
- Marketing 69
- General Social Sciences 17
- Sociology and Political Science 194
Countries citing papers authored by Massimo Airoldi
This map shows the geographic impact of Massimo Airoldi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Massimo Airoldi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Massimo Airoldi more than expected).
Fields of papers citing papers by Massimo Airoldi
This network shows the impact of papers produced by Massimo Airoldi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Massimo Airoldi. The network helps show where Massimo Airoldi may publish in the future.
Co-authors
The 10 scholars most cited alongside Massimo Airoldi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 103 | |
| 2 | 2018 | 90 | |
| 3 | 2017 | 60 | |
| 4 | 2022 | 55 | |
| 5 | 2015 | 30 | |
| 6 | 2019 | 30 | |
| 7 | 2021 | 29 | |
| 8 | Machine habitus toward a sociology of algorithms | 2022 | 20 |
| 9 | 2021 | 19 | |
| 10 | 2023 | 4 | |
| 11 | 2018 | 2 | |
| 12 | 2015 | 1 | |
| 13 | 2016 | 1 | |
| 14 | Web & social media : Le tecniche di analisi | 2017 | 1 |
| 15 | 2018 | 1 | |
| 16 | 2020 | 1 | |
| 17 | 2022 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2016 | 0 | |
| 20 | 2023 | 0 |
About Massimo Airoldi
Massimo Airoldi is a scholar working on Safety Research, Music, General Social Sciences, Sociology and Political Science and Communication, having authored 24 papers that have together received 449 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (8 papers), Digital Marketing and Social Media (5 papers), Music History and Culture (4 papers), Recommender Systems and Techniques (3 papers), Computational and Text Analysis Methods (3 papers), Consumer Behavior in Brand Consumption and Identification (3 papers), Digital Media and Philosophy (2 papers) and Media and Digital Communication (2 papers). The work is most often cited by research in Communication (96 citations), Music (43 citations), Marketing (69 citations), General Social Sciences (17 citations) and Sociology and Political Science (194 citations). Massimo Airoldi has collaborated with scholars based in Italy, France and United Kingdom. Frequent co-authors include Davide Beraldo, Alessandro Gandini, Joonas Rokka, Mauro Barisione, Asimina Michailidou, Adam Arvidsson, Alessandro Caliandro, Lotta K. Harju, Francesco Molteni and Sergio Splendore. Their work appears in journals such as Poetics, Consumption Markets & Culture, Information Communication & Society, Journal of Macromarketing and Big Data & Society.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.