US EditionSocial Media Post Sparks Communal Clashes in Pune Village
YAVAT VILLAGE, PUNE DISTRICT, MAHARASHTRA, INDIA, AUG 1 – Police arrested 18 people and registered five FIRs after communal violence erupted over a social media post linked to a controversial rape allegation, police said.
- On August 1, 2025, violence broke out in Yavat village, Pune district, triggered by a viral social media update regarding a purported sexual assault case in Madhya Pradesh.
- The unrest followed a controversial post by an outsider, a daily wage laborer from Nanded, which included a collage alleging the rape of minor girls by a priest, and tensions had been rising since a statue of Shivaji was desecrated on July 26.
- During the violence, mobs vandalized two-wheelers, cars, a bakery, and a religious prayer place while police responded with tear gas and lathi charge to disperse protestors, detaining 17 individuals and filing five cases.
- Superintendent of Police Sandip Gill stated the situation is now under control, with prohibitory orders banning gatherings in Yavat from August 1 to 3, and police investigations continue against suspects involved in stone pelting and arson.
- Authorities, including Chief Minister Devendra Fadnavis and IG Sunil Phulari, denounced the inflammatory post and vowed to take firm measures against individuals responsible for inciting hostility or violence, while local officials and community members organized demonstrations to protest the statue vandalism and promote harmony.
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Social Media Post Sparks Communal Clashes in Pune Village
Communal clashes erupted in Pune's Yavat village after an objectionable social media post led to arson and property damage. Police have registered multiple cases, detaining 17 individuals and arresting the post's uploader. Authorities have deployed preventive measures and emphasize that strict action will be taken against those spreading inflammatory content.
·India
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Coverage Details
Total News Sources9
Leaning Left3Leaning Right1Center1Last UpdatedBias Distribution60% Left
Bias Distribution
- 60% of the sources lean Left
60% Left
L 60%
C 20%
R 20%
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