{'fraction_non_alphanumeric': 0.030871003307607496, 'fraction_numerical': 0.004410143329658214, 'mean_word_length': 4.7834394904458595, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Zealots' effect on opinion dynamics in complex networks

In this paper, we study zealots' effects on social networks. Our social network is based on scale-free networks using Barabasi–Albert method and random networks using Erdős–Rényi method. We used a pre-studied modified Voter model that includes zealots, individuals who never change their opinions. We chose prominent individuals (i.e. hubs) as zealots. In this way we first chose important individuals with high degree (hubs); second, individuals with high closeness. And then examined the consensus time compared with that zealots are chosen as non-important individuals. We found that the time to get to the consensus state in social networks is the same for different numbers of zealots but with the same degrees of contamination with zealotry. For example, one zealot's effect with a degree of 64 is same to 8 zealots' effects with a degree of 8.