Artificial Intelligence (AI) in Advertising
Nowadays, information technology is not only widely used in all walks of life but also fully applied in the marketing and advertisement sector. In particular, Artificial Intelligence (AI) has received growing attention worldwide because of its impact on advertising. However, it remains unclear how s...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Ediciones Universidad de Salamanca
2023-01-01
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| Series: | Advances in Distributed Computing and Artificial Intelligence Journal |
| Subjects: | |
| Online Access: | https://revistas.usal.es/cinco/index.php/2255-2863/article/view/28331 |
| _version_ | 1797943635266764800 |
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| author | Metin Argan Halime Dinç Sabri Kaya Mehpare Tokay Argan |
| author_facet | Metin Argan Halime Dinç Sabri Kaya Mehpare Tokay Argan |
| author_sort | Metin Argan |
| collection | DOAJ |
| description | Nowadays, information technology is not only widely used in all walks of life but also fully applied in the marketing and advertisement sector. In particular, Artificial Intelligence (AI) has received growing attention worldwide because of its impact on advertising. However, it remains unclear how social media users react to AI advertisements. The purpose of this study is to examine the behavior of social media users towards AI-based advertisements. This study used a qualitative method, including a semi-structured interview. A total of 23 semi-structured interviews were conducted with social media users aged 18 and over, using a purposive sampling method. The interviews lasted between 27.05–50.39 minutes on average (Mean: 37.48 SD: 6.25) between August and October 2021. We categorized the findings of the current qualitative research into three main process themes: I) reception; II) diving; and III) break-point. While 'reception' covers positive and negative sub-themes, 'diving' includes three themes: comparison, timesaving, and leaping. The final theme, 'break-point', represents the decision-making stage and includes negative or positive opinions. This study provides content producers, social media practitioners, marketing managers, advertising industry, AI researchers, and academics with many insights into AI advertising. |
| first_indexed | 2024-04-10T20:27:17Z |
| format | Article |
| id | doaj.art-410b893623dd47f3b11445cff6d7d363 |
| institution | Directory Open Access Journal |
| issn | 2255-2863 |
| language | English |
| last_indexed | 2024-04-10T20:27:17Z |
| publishDate | 2023-01-01 |
| publisher | Ediciones Universidad de Salamanca |
| record_format | Article |
| series | Advances in Distributed Computing and Artificial Intelligence Journal |
| spelling | doaj.art-410b893623dd47f3b11445cff6d7d3632023-01-25T08:48:07ZengEdiciones Universidad de SalamancaAdvances in Distributed Computing and Artificial Intelligence Journal2255-28632023-01-0111333134810.14201/adcaij.2833133792Artificial Intelligence (AI) in AdvertisingMetin Argan0Halime Dinç1Sabri Kaya2https://orcid.org/0000-0002-9418-6920Mehpare Tokay Argan3Eskisehir Technical UniversityAfyon Kocatepe UniversityKirikkale UniversityBilecik Seyh Edebali UniversityNowadays, information technology is not only widely used in all walks of life but also fully applied in the marketing and advertisement sector. In particular, Artificial Intelligence (AI) has received growing attention worldwide because of its impact on advertising. However, it remains unclear how social media users react to AI advertisements. The purpose of this study is to examine the behavior of social media users towards AI-based advertisements. This study used a qualitative method, including a semi-structured interview. A total of 23 semi-structured interviews were conducted with social media users aged 18 and over, using a purposive sampling method. The interviews lasted between 27.05–50.39 minutes on average (Mean: 37.48 SD: 6.25) between August and October 2021. We categorized the findings of the current qualitative research into three main process themes: I) reception; II) diving; and III) break-point. While 'reception' covers positive and negative sub-themes, 'diving' includes three themes: comparison, timesaving, and leaping. The final theme, 'break-point', represents the decision-making stage and includes negative or positive opinions. This study provides content producers, social media practitioners, marketing managers, advertising industry, AI researchers, and academics with many insights into AI advertising.https://revistas.usal.es/cinco/index.php/2255-2863/article/view/28331artificial intelligenceadvertisingsocial media userai ads effects |
| spellingShingle | Metin Argan Halime Dinç Sabri Kaya Mehpare Tokay Argan Artificial Intelligence (AI) in Advertising Advances in Distributed Computing and Artificial Intelligence Journal artificial intelligence advertising social media user ai ads effects |
| title | Artificial Intelligence (AI) in Advertising |
| title_full | Artificial Intelligence (AI) in Advertising |
| title_fullStr | Artificial Intelligence (AI) in Advertising |
| title_full_unstemmed | Artificial Intelligence (AI) in Advertising |
| title_short | Artificial Intelligence (AI) in Advertising |
| title_sort | artificial intelligence ai in advertising |
| topic | artificial intelligence advertising social media user ai ads effects |
| url | https://revistas.usal.es/cinco/index.php/2255-2863/article/view/28331 |
| work_keys_str_mv | AT metinargan artificialintelligenceaiinadvertising AT halimedinc artificialintelligenceaiinadvertising AT sabrikaya artificialintelligenceaiinadvertising AT mehparetokayargan artificialintelligenceaiinadvertising |